Search (93 results, page 1 of 5)

  • × theme_ss:"Suchmaschinen"
  • × year_i:[2010 TO 2020}
  1. Fluhr, C.: Crosslingual access to photo databases (2012) 0.07 
    0.069903165 = product of:
  0.11184507 = sum of:
    0.025048172 = weight(_text_:retrieval in 93) [ClassicSimilarity], result of:
      0.025048172 = score(doc=93,freq=2.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.20052543 = fieldWeight in 93, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=93)
    0.044457585 = weight(_text_:use in 93) [ClassicSimilarity], result of:
      0.044457585 = score(doc=93,freq=6.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.35158852 = fieldWeight in 93, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=93)
    0.018933605 = weight(_text_:of in 93) [ClassicSimilarity], result of:
      0.018933605 = score(doc=93,freq=16.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.2932045 = fieldWeight in 93, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=93)
    0.006621159 = product of:
      0.013242318 = sum of:
        0.013242318 = weight(_text_:on in 93) [ClassicSimilarity], result of:
          0.013242318 = score(doc=93,freq=2.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.14580199 = fieldWeight in 93, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=93)
      0.5 = coord(1/2)
    0.016784549 = product of:
      0.033569098 = sum of:
        0.033569098 = weight(_text_:22 in 93) [ClassicSimilarity], result of:
          0.033569098 = score(doc=93,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.23214069 = fieldWeight in 93, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=93)
      0.5 = coord(1/2)
  0.625 = coord(5/8)
    Abstract
    This paper is about search of photos in photo databases of agencies which sell photos over the Internet. The problem is far from the behavior of photo databases managed by librarians and also far from the corpora generally used for research purposes. The descriptions use mainly single words and it is well known that it is not the best way to have a good search. This increases the problem of semantic ambiguity. This problem of semantic ambiguity is crucial for cross-language querying. On the other hand, users are not aware of documentation techniques and use generally very simple queries but want to get precise answers. This paper gives the experience gained in a 3 year use (2006-2008) of a cross-language access to several of the main international commercial photo databases. The languages used were French, English, and German.
    Date
    17. 4.2012 14:25:22
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  2. Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012) 0.06 
    0.06046891 = product of:
  0.09675025 = sum of:
    0.020873476 = weight(_text_:retrieval in 109) [ClassicSimilarity], result of:
      0.020873476 = score(doc=109,freq=2.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.16710453 = fieldWeight in 109, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=109)
    0.037047986 = weight(_text_:use in 109) [ClassicSimilarity], result of:
      0.037047986 = score(doc=109,freq=6.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.29299045 = fieldWeight in 109, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.0390625 = fieldNorm(doc=109)
    0.019324033 = weight(_text_:of in 109) [ClassicSimilarity], result of:
      0.019324033 = score(doc=109,freq=24.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.2992506 = fieldWeight in 109, product of:
          4.8989797 = tf(freq=24.0), with freq of:
            24.0 = termFreq=24.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=109)
    0.0055176322 = product of:
      0.0110352645 = sum of:
        0.0110352645 = weight(_text_:on in 109) [ClassicSimilarity], result of:
          0.0110352645 = score(doc=109,freq=2.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.121501654 = fieldWeight in 109, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=109)
      0.5 = coord(1/2)
    0.013987125 = product of:
      0.02797425 = sum of:
        0.02797425 = weight(_text_:22 in 109) [ClassicSimilarity], result of:
          0.02797425 = score(doc=109,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.19345059 = fieldWeight in 109, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=109)
      0.5 = coord(1/2)
  0.625 = coord(5/8)
    Abstract
    This chapter shows that the wider use of Web search engines, reconsidering the theoretical and methodological frameworks to grasp new information practices. Beginning with an overview of the recent challenges implied by the dynamic nature of the Web, this chapter then traces the information behavior related concepts in order to present the different approaches from the user perspective. The authors pay special attention to the concept of "information practice" and other related concepts such as "use", "activity", and "behavior" largely used in the literature but not always strictly defined. The authors provide an overview of user-oriented studies that are meaningful to understand the different contexts of use of electronic information access systems, focusing on five approaches: the system-oriented approaches, the theories of information seeking, the cognitive and psychological approaches, the management science approaches, and the marketing approaches. Future directions of work are then shaped, including social searching and the ethical, cultural, and political dimensions of Web search engines. The authors conclude considering the importance of Critical theory to better understand the role of Web Search engines in our modern society.
    Date
    20. 4.2012 13:22:37
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  3. Roux, M.: Metadata for search engines : what can be learned from e-Sciences? (2012) 0.06 
    0.056946788 = product of:
  0.113893576 = sum of:
    0.035423465 = weight(_text_:retrieval in 96) [ClassicSimilarity], result of:
      0.035423465 = score(doc=96,freq=4.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.2835858 = fieldWeight in 96, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=96)
    0.025667597 = weight(_text_:use in 96) [ClassicSimilarity], result of:
      0.025667597 = score(doc=96,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.20298971 = fieldWeight in 96, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=96)
    0.014968331 = weight(_text_:of in 96) [ClassicSimilarity], result of:
      0.014968331 = score(doc=96,freq=10.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.23179851 = fieldWeight in 96, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=96)
    0.037834182 = product of:
      0.075668365 = sum of:
        0.075668365 = weight(_text_:computers in 96) [ClassicSimilarity], result of:
          0.075668365 = score(doc=96,freq=2.0), product of:
            0.21710795 = queryWeight, product of:
              5.257537 = idf(docFreq=625, maxDocs=44218)
              0.041294612 = queryNorm
            0.34852874 = fieldWeight in 96, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.257537 = idf(docFreq=625, maxDocs=44218)
              0.046875 = fieldNorm(doc=96)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    E-sciences are data-intensive sciences that make a large use of the Web to share, collect, and process data. In this context, primary scientific data is becoming a new challenging issue as data must be extensively described (1) to account for empiric conditions and results that allow interpretation and/or analyses and (2) to be understandable by computers used for data storage and information retrieval. With this respect, metadata is a focal point whatever it is considered from the point of view of the user to visualize and exploit data as well as this of the search tools to find and retrieve information. Numerous disciplines are concerned with the issues of describing complex observations and addressing pertinent knowledge. In this paper, similarities and differences in data description and exploration strategies among disciplines in e-sciences are examined.
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  4. Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012) 0.05 
    0.04737303 = product of:
  0.09474606 = sum of:
    0.050096344 = weight(_text_:retrieval in 108) [ClassicSimilarity], result of:
      0.050096344 = score(doc=108,freq=8.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.40105087 = fieldWeight in 108, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=108)
    0.016396983 = weight(_text_:of in 108) [ClassicSimilarity], result of:
      0.016396983 = score(doc=108,freq=12.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.25392252 = fieldWeight in 108, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=108)
    0.011468184 = product of:
      0.022936368 = sum of:
        0.022936368 = weight(_text_:on in 108) [ClassicSimilarity], result of:
          0.022936368 = score(doc=108,freq=6.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.25253648 = fieldWeight in 108, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=108)
      0.5 = coord(1/2)
    0.016784549 = product of:
      0.033569098 = sum of:
        0.033569098 = weight(_text_:22 in 108) [ClassicSimilarity], result of:
          0.033569098 = score(doc=108,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.23214069 = fieldWeight in 108, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=108)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    The explosion of the information available on the Internet has made traditional information retrieval systems, characterized by one size fits all approaches, less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval (CIR) which relies on various sources of evidence issued from the user's search background and environment, in order to improve the retrieval accuracy. This chapter focuses on mobile context, highlights challenges they present for IR, and gives an overview of CIR approaches applied in this environment. Then, the authors present an approach to personalize search results for mobile users by exploiting both cognitive and spatio-temporal contexts. The experimental evaluation undertaken in front of Yahoo search shows that the approach improves the quality of top search result lists and enhances search result precision.
    Date
    20. 4.2012 13:19:22
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  5. Croft, W.B.; Metzler, D.; Strohman, T.: Search engines : information retrieval in practice (2010) 0.04 
    0.044349354 = product of:
  0.11826494 = sum of:
    0.07920927 = weight(_text_:retrieval in 2605) [ClassicSimilarity], result of:
      0.07920927 = score(doc=2605,freq=20.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.63411707 = fieldWeight in 2605, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=2605)
    0.025667597 = weight(_text_:use in 2605) [ClassicSimilarity], result of:
      0.025667597 = score(doc=2605,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.20298971 = fieldWeight in 2605, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=2605)
    0.013388081 = weight(_text_:of in 2605) [ClassicSimilarity], result of:
      0.013388081 = score(doc=2605,freq=8.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.20732689 = fieldWeight in 2605, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=2605)
  0.375 = coord(3/8)
    Abstract
    For introductory information retrieval courses at the undergraduate and graduate level in computer science, information science and computer engineering departments. Written by a leader in the field of information retrieval, Search Engines: Information Retrieval in Practice, is designed to give undergraduate students the understanding and tools they need to evaluate, compare and modify search engines. Coverage of the underlying IR and mathematical models reinforce key concepts. The book's numerous programming exercises make extensive use of Galago, a Java-based open source search engine. SUPPLEMENTS / Extensive lecture slides (in PDF and PPT format) / Solutions to selected end of chapter problems (Instructors only) / Test collections for exercises / Galago search engine
    LCSH
    Information retrieval
    Information Storage and Retrieval
    RSWK
    Suchmaschine / Information Retrieval
    Subject
    Suchmaschine / Information Retrieval
    Information retrieval
    Information Storage and Retrieval
  6. Huvila, I.: Affective capitalism of knowing and the society of search engine (2016) 0.04 
    0.04116037 = product of:
  0.08232074 = sum of:
    0.025667597 = weight(_text_:use in 3246) [ClassicSimilarity], result of:
      0.025667597 = score(doc=3246,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.20298971 = fieldWeight in 3246, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=3246)
    0.028400408 = weight(_text_:of in 3246) [ClassicSimilarity], result of:
      0.028400408 = score(doc=3246,freq=36.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.43980673 = fieldWeight in 3246, product of:
          6.0 = tf(freq=36.0), with freq of:
            36.0 = termFreq=36.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=3246)
    0.011468184 = product of:
      0.022936368 = sum of:
        0.022936368 = weight(_text_:on in 3246) [ClassicSimilarity], result of:
          0.022936368 = score(doc=3246,freq=6.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.25253648 = fieldWeight in 3246, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=3246)
      0.5 = coord(1/2)
    0.016784549 = product of:
      0.033569098 = sum of:
        0.033569098 = weight(_text_:22 in 3246) [ClassicSimilarity], result of:
          0.033569098 = score(doc=3246,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.23214069 = fieldWeight in 3246, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3246)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    Purpose The purpose of this paper is to discuss the affective premises and economics of the influence of search engines on knowing and informing in the contemporary society. Design/methodology/approach A conceptual discussion of the affective premises and framings of the capitalist economics of knowing is presented. Findings The main proposition of this text is that the exploitation of affects is entwined in the competing market and emancipatory discourses and counter-discourses both as intentional interventions, and perhaps even more significantly, as unintentional influences that shape the ways of knowing in the peripheries of the regime that shape cultural constellations of their own. Affective capitalism bounds and frames our ways of knowing in ways that are difficult to anticipate and read even from the context of the regime itself. Originality/value In the relatively extensive discussion on the role of affects in the contemporary capitalism, influence of affects on knowing and their relation to search engine use has received little explicit attention so far.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 68(2016) no.5, S.566-588
  7. Next generation search engines : advanced models for information retrieval (2012) 0.04 
    0.040498387 = product of:
  0.080996774 = sum of:
    0.0390507 = weight(_text_:retrieval in 357) [ClassicSimilarity], result of:
      0.0390507 = score(doc=357,freq=28.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.31262395 = fieldWeight in 357, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.01953125 = fieldNorm(doc=357)
    0.021389665 = weight(_text_:use in 357) [ClassicSimilarity], result of:
      0.021389665 = score(doc=357,freq=8.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.1691581 = fieldWeight in 357, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.01953125 = fieldNorm(doc=357)
    0.015778005 = weight(_text_:of in 357) [ClassicSimilarity], result of:
      0.015778005 = score(doc=357,freq=64.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.24433708 = fieldWeight in 357, product of:
          8.0 = tf(freq=64.0), with freq of:
            64.0 = termFreq=64.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.01953125 = fieldNorm(doc=357)
    0.00477841 = product of:
      0.00955682 = sum of:
        0.00955682 = weight(_text_:on in 357) [ClassicSimilarity], result of:
          0.00955682 = score(doc=357,freq=6.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.10522352 = fieldWeight in 357, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.01953125 = fieldNorm(doc=357)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    The main goal of this book is to transfer new research results from the fields of advanced computer sciences and information science to the design of new search engines. The readers will have a better idea of the new trends in applied research. The achievement of relevant, organized, sorted, and workable answers- to name but a few - from a search is becoming a daily need for enterprises and organizations, and, to a greater extent, for anyone. It does not consist of getting access to structural information as in standard databases; nor does it consist of searching information strictly by way of a combination of key words. It goes far beyond that. Whatever its modality, the information sought should be identified by the topics it contains, that is to say by its textual, audio, video or graphical contents. This is not a new issue. However, recent technological advances have completely changed the techniques being used. New Web technologies, the emergence of Intranet systems and the abundance of information on the Internet have created the need for efficient search and information access tools.
    Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.
    With the rapid growth of web-based applications, such as search engines, Facebook, and Twitter, the development of effective and personalized information retrieval techniques and of user interfaces is essential. The amount of shared information and of social networks has also considerably grown, requiring metadata for new sources of information, like Wikipedia and ODP. These metadata have to provide classification information for a wide range of topics, as well as for social networking sites like Twitter, and Facebook, each of which provides additional preferences, tagging information and social contexts. Due to the explosion of social networks and other metadata sources, it is an opportune time to identify ways to exploit such metadata in IR tasks such as user modeling, query understanding, and personalization, to name a few. Although the use of traditional metadata such as html text, web page titles, and anchor text is fairly well-understood, the use of category information, user behavior data, and geographical information is just beginning to be studied. This book is intended for scientists and decision-makers who wish to gain working knowledge about search engines in order to evaluate available solutions and to dialogue with software and data providers.
    Content
    Enthält die Beiträge: Das, A., A. Jain: Indexing the World Wide Web: the journey so far. Ke, W.: Decentralized search and the clustering paradox in large scale information networks. Roux, M.: Metadata for search engines: what can be learned from e-Sciences? Fluhr, C.: Crosslingual access to photo databases. Djioua, B., J.-P. Desclés u. M. Alrahabi: Searching and mining with semantic categories. Ghorbel, H., A. Bahri u. R. Bouaziz: Fuzzy ontologies building platform for Semantic Web: FOB platform. Lassalle, E., E. Lassalle: Semantic models in information retrieval. Berry, M.W., R. Esau u. B. Kiefer: The use of text mining techniques in electronic discovery for legal matters. Sleem-Amer, M., I. Bigorgne u. S. Brizard u.a.: Intelligent semantic search engines for opinion and sentiment mining. Hoeber, O.: Human-centred Web search.
    Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.
    LCSH
    Information retrieval
    Information retrieval / Research
    Information storage and retrieval systems / Research
    Subject
    Information retrieval
    Information retrieval / Research
    Information storage and retrieval systems / Research
  8. White, R.W.: Interactions with search systems (2016) 0.04 
    0.03836269 = product of:
  0.07672538 = sum of:
    0.036153924 = weight(_text_:retrieval in 3612) [ClassicSimilarity], result of:
      0.036153924 = score(doc=3612,freq=6.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.28943354 = fieldWeight in 3612, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3612)
    0.021389665 = weight(_text_:use in 3612) [ClassicSimilarity], result of:
      0.021389665 = score(doc=3612,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.1691581 = fieldWeight in 3612, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3612)
    0.013664153 = weight(_text_:of in 3612) [ClassicSimilarity], result of:
      0.013664153 = score(doc=3612,freq=12.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.21160212 = fieldWeight in 3612, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3612)
    0.0055176322 = product of:
      0.0110352645 = sum of:
        0.0110352645 = weight(_text_:on in 3612) [ClassicSimilarity], result of:
          0.0110352645 = score(doc=3612,freq=2.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.121501654 = fieldWeight in 3612, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3612)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    Information seeking is a fundamental human activity. In the modern world, it is frequently conducted through interactions with search systems. The retrieval and comprehension of information returned by these systems is a key part of decision making and action in a broad range of settings. Advances in data availability coupled with new interaction paradigms, and mobile and cloud computing capabilities, have created a broad range of new opportunities for information access and use. In this comprehensive book for professionals, researchers, and students involved in search system design and evaluation, search expert Ryen White discusses how search systems can capitalize on new capabilities and how next-generation systems must support higher order search activities such as task completion, learning, and decision making. He outlines the implications of these changes for the evolution of search evaluation, as well as challenges that extend beyond search systems in areas such as privacy and societal benefit.
    RSWK
    Information Retrieval
    Subject
    Information Retrieval
  9. Sachse, J.: ¬The influence of snippet length on user behavior in mobile web search (2019) 0.04 
    0.03571692 = product of:
  0.07143384 = sum of:
    0.030249555 = weight(_text_:use in 5493) [ClassicSimilarity], result of:
      0.030249555 = score(doc=5493,freq=4.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.23922569 = fieldWeight in 5493, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5493)
    0.017640345 = weight(_text_:of in 5493) [ClassicSimilarity], result of:
      0.017640345 = score(doc=5493,freq=20.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.27317715 = fieldWeight in 5493, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5493)
    0.00955682 = product of:
      0.01911364 = sum of:
        0.01911364 = weight(_text_:on in 5493) [ClassicSimilarity], result of:
          0.01911364 = score(doc=5493,freq=6.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.21044704 = fieldWeight in 5493, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5493)
      0.5 = coord(1/2)
    0.013987125 = product of:
      0.02797425 = sum of:
        0.02797425 = weight(_text_:22 in 5493) [ClassicSimilarity], result of:
          0.02797425 = score(doc=5493,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.19345059 = fieldWeight in 5493, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5493)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    Purpose Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering informative snippets and optimal use of space. One factor clearly influencing this trade-off is snippet length. The purpose of this paper is to find out what snippet size to use in mobile web search. Design/methodology/approach For this purpose, an eye-tracking experiment was conducted showing participants search interfaces with snippets of one, three or five lines on a mobile device to analyze 17 dependent variables. In total, 31 participants took part in the study. Each of the participants solved informational and navigational tasks. Findings Results indicate a strong influence of page fold on scrolling behavior and attention distribution across search results. Regardless of query type, short snippets seem to provide too little information about the result, so that search performance and subjective measures are negatively affected. Long snippets of five lines lead to better performance than medium snippets for navigational queries, but to worse performance for informational queries. Originality/value Although space in mobile search is limited, this study shows that longer snippets improve usability and user experience. It further emphasizes that page fold plays a stronger role in mobile than in desktop search for attention distribution.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.3, S.325-343
  10. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.04 
    0.0351057 = product of:
  0.0702114 = sum of:
    0.020873476 = weight(_text_:retrieval in 444) [ClassicSimilarity], result of:
      0.020873476 = score(doc=444,freq=2.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.16710453 = fieldWeight in 444, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=444)
    0.02431554 = weight(_text_:of in 444) [ClassicSimilarity], result of:
      0.02431554 = score(doc=444,freq=38.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.37654874 = fieldWeight in 444, product of:
          6.164414 = tf(freq=38.0), with freq of:
            38.0 = termFreq=38.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=444)
    0.0110352645 = product of:
      0.022070529 = sum of:
        0.022070529 = weight(_text_:on in 444) [ClassicSimilarity], result of:
          0.022070529 = score(doc=444,freq=8.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.24300331 = fieldWeight in 444, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=444)
      0.5 = coord(1/2)
    0.013987125 = product of:
      0.02797425 = sum of:
        0.02797425 = weight(_text_:22 in 444) [ClassicSimilarity], result of:
          0.02797425 = score(doc=444,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.19345059 = fieldWeight in 444, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=444)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    This paper aims to review the fiercely discussed question of whether the ranking of Wikipedia articles in search engines is justified by the quality of the articles. After an overview of current research on information quality in Wikipedia, a summary of the extended discussion on the quality of encyclopedic entries in general is given. On this basis, a heuristic method for evaluating Wikipedia entries is developed and applied to Wikipedia articles that scored highly in a search engine retrieval effectiveness test and compared with the relevance judgment of jurors. In all search engines tested, Wikipedia results are unanimously judged better by the jurors than other results on the corresponding results position. Relevance judgments often roughly correspond with the results from the heuristic evaluation. Cases in which high relevance judgments are not in accordance with the comparatively low score from the heuristic evaluation are interpreted as an indicator of a high degree of trust in Wikipedia. One of the systemic shortcomings of Wikipedia lies in its necessarily incoherent user model. A further tuning of the suggested criteria catalog, for instance, the different weighing of the supplied criteria, could serve as a starting point for a user model differentiated evaluation of Wikipedia articles. Approved methods of quality evaluation of reference works are applied to Wikipedia articles and integrated with the question of search engine evaluation.
    Date
    30. 9.2012 19:27:22
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.1, S.117-132
  11. Gossen, T.: Search engines for children : search user interfaces and information-seeking behaviour (2016) 0.03 
    0.0340323 = product of:
  0.0680646 = sum of:
    0.035790555 = weight(_text_:retrieval in 2752) [ClassicSimilarity], result of:
      0.035790555 = score(doc=2752,freq=12.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.28652456 = fieldWeight in 2752, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2752)
    0.017020877 = weight(_text_:of in 2752) [ClassicSimilarity], result of:
      0.017020877 = score(doc=2752,freq=38.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.2635841 = fieldWeight in 2752, product of:
          6.164414 = tf(freq=38.0), with freq of:
            38.0 = termFreq=38.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2752)
    0.0054621776 = product of:
      0.010924355 = sum of:
        0.010924355 = weight(_text_:on in 2752) [ClassicSimilarity], result of:
          0.010924355 = score(doc=2752,freq=4.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.120280504 = fieldWeight in 2752, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2752)
      0.5 = coord(1/2)
    0.009790987 = product of:
      0.019581974 = sum of:
        0.019581974 = weight(_text_:22 in 2752) [ClassicSimilarity], result of:
          0.019581974 = score(doc=2752,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.1354154 = fieldWeight in 2752, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2752)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    The doctoral thesis of Tatiana Gossen formulates criteria and guidelines on how to design the user interfaces of search engines for children. In her work, the author identifies the conceptual challenges based on own and previous user studies and addresses the changing characteristics of the users by providing a means of adaptation. Additionally, a novel type of search result visualisation for children with cartoon style characters is developed taking children's preference for visual information into account.
    Content
    Inhalt: Acknowledgments; Abstract; Zusammenfassung; Contents; List of Figures; List of Tables; List of Acronyms; Chapter 1 Introduction ; 1.1 Research Questions; 1.2 Thesis Outline; Part I Fundamentals ; Chapter 2 Information Retrieval for Young Users ; 2.1 Basics of Information Retrieval; 2.1.1 Architecture of an IR System; 2.1.2 Relevance Ranking; 2.1.3 Search User Interfaces; 2.1.4 Targeted Search Engines; 2.2 Aspects of Child Development Relevant for Information Retrieval Tasks; 2.2.1 Human Cognitive Development; 2.2.2 Information Processing Theory; 2.2.3 Psychosocial Development 2.3 User Studies and Evaluation2.3.1 Methods in User Studies; 2.3.2 Types of Evaluation; 2.3.3 Evaluation with Children; 2.4 Discussion; Chapter 3 State of the Art ; 3.1 Children's Information-Seeking Behaviour; 3.1.1 Querying Behaviour; 3.1.2 Search Strategy; 3.1.3 Navigation Style; 3.1.4 User Interface; 3.1.5 Relevance Judgement; 3.2 Existing Algorithms and User Interface Concepts for Children; 3.2.1 Query; 3.2.2 Content; 3.2.3 Ranking; 3.2.4 Search Result Visualisation; 3.3 Existing Information Retrieval Systems for Children; 3.3.1 Digital Book Libraries; 3.3.2 Web Search Engines 3.4 Summary and DiscussionPart II Studying Open Issues ; Chapter 4 Usability of Existing Search Engines for Young Users ; 4.1 Assessment Criteria; 4.1.1 Criteria for Matching the Motor Skills; 4.1.2 Criteria for Matching the Cognitive Skills; 4.2 Results; 4.2.1 Conformance with Motor Skills; 4.2.2 Conformance with the Cognitive Skills; 4.2.3 Presentation of Search Results; 4.2.4 Browsing versus Searching; 4.2.5 Navigational Style; 4.3 Summary and Discussion; Chapter 5 Large-scale Analysis of Children's Queries and Search Interactions; 5.1 Dataset; 5.2 Results; 5.3 Summary and Discussion Chapter 6 Differences in Usability and Perception of Targeted Web Search Engines between Children and Adults 6.1 Related Work; 6.2 User Study; 6.3 Study Results; 6.4 Summary and Discussion; Part III Tackling the Challenges ; Chapter 7 Search User Interface Design for Children ; 7.1 Conceptual Challenges and Possible Solutions; 7.2 Knowledge Journey Design; 7.3 Evaluation; 7.3.1 Study Design; 7.3.2 Study Results; 7.4 Voice-Controlled Search: Initial Study; 7.4.1 User Study; 7.5 Summary and Discussion; Chapter 8 Addressing User Diversity ; 8.1 Evolving Search User Interface 8.1.1 Mapping Function8.1.2 Evolving Skills; 8.1.3 Detection of User Abilities; 8.1.4 Design Concepts; 8.2 Adaptation of a Search User Interface towards User Needs; 8.2.1 Design & Implementation; 8.2.2 Search Input; 8.2.3 Result Output; 8.2.4 General Properties; 8.2.5 Configuration and Further Details; 8.3 Evaluation; 8.3.1 Study Design; 8.3.2 Study Results; 8.3.3 Preferred UI Settings; 8.3.4 User satisfaction; 8.4 Knowledge Journey Exhibit; 8.4.1 Hardware; 8.4.2 Frontend; 8.4.3 Backend; 8.5 Summary and Discussion; Chapter 9 Supporting Visual Searchers in Processing Search Results 9.1 Related Work
    Date
    1. 2.2016 18:25:22
    LCSH
    Information storage and retrieval
    Subject
    Information storage and retrieval
  12. Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011) 0.03 
    0.032742057 = product of:
  0.065484114 = sum of:
    0.020873476 = weight(_text_:retrieval in 438) [ClassicSimilarity], result of:
      0.020873476 = score(doc=438,freq=2.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.16710453 = fieldWeight in 438, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=438)
    0.021389665 = weight(_text_:use in 438) [ClassicSimilarity], result of:
      0.021389665 = score(doc=438,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.1691581 = fieldWeight in 438, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.0390625 = fieldNorm(doc=438)
    0.013664153 = weight(_text_:of in 438) [ClassicSimilarity], result of:
      0.013664153 = score(doc=438,freq=12.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.21160212 = fieldWeight in 438, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=438)
    0.00955682 = product of:
      0.01911364 = sum of:
        0.01911364 = weight(_text_:on in 438) [ClassicSimilarity], result of:
          0.01911364 = score(doc=438,freq=6.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.21044704 = fieldWeight in 438, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=438)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.
  13. Chen, L.-C.: Next generation search engine for the result clustering technology (2012) 0.03 
    0.032425433 = product of:
  0.06485087 = sum of:
    0.025048172 = weight(_text_:retrieval in 105) [ClassicSimilarity], result of:
      0.025048172 = score(doc=105,freq=2.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.20052543 = fieldWeight in 105, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=105)
    0.016396983 = weight(_text_:of in 105) [ClassicSimilarity], result of:
      0.016396983 = score(doc=105,freq=12.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.25392252 = fieldWeight in 105, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=105)
    0.006621159 = product of:
      0.013242318 = sum of:
        0.013242318 = weight(_text_:on in 105) [ClassicSimilarity], result of:
          0.013242318 = score(doc=105,freq=2.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.14580199 = fieldWeight in 105, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=105)
      0.5 = coord(1/2)
    0.016784549 = product of:
      0.033569098 = sum of:
        0.033569098 = weight(_text_:22 in 105) [ClassicSimilarity], result of:
          0.033569098 = score(doc=105,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.23214069 = fieldWeight in 105, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=105)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    Result clustering has recently attracted a lot of attention to provide the users with a succinct overview of relevant search results than traditional search engines. This chapter proposes a mixed clustering method to organize all returned search results into a hierarchical tree structure. The clustering method accomplishes two main tasks, one is label construction and the other is tree building. This chapter uses precision to measure the quality of clustering results. According to the results of experiments, the author preliminarily concluded that the performance of the system is better than many other well-known commercial and academic systems. This chapter makes several contributions. First, it presents a high performance system based on the clustering method. Second, it develops a divisive hierarchical clustering algorithm to organize all returned snippets into hierarchical tree structure. Third, it performs a wide range of experimental analyses to show that almost all commercial systems are significantly better than most current academic systems.
    Date
    17. 4.2012 15:22:11
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  14. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.03 
    0.032026198 = product of:
  0.064052396 = sum of:
    0.021389665 = weight(_text_:use in 5288) [ClassicSimilarity], result of:
      0.021389665 = score(doc=5288,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.1691581 = fieldWeight in 5288, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5288)
    0.017640345 = weight(_text_:of in 5288) [ClassicSimilarity], result of:
      0.017640345 = score(doc=5288,freq=20.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.27317715 = fieldWeight in 5288, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5288)
    0.0110352645 = product of:
      0.022070529 = sum of:
        0.022070529 = weight(_text_:on in 5288) [ClassicSimilarity], result of:
          0.022070529 = score(doc=5288,freq=8.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.24300331 = fieldWeight in 5288, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5288)
      0.5 = coord(1/2)
    0.013987125 = product of:
      0.02797425 = sum of:
        0.02797425 = weight(_text_:22 in 5288) [ClassicSimilarity], result of:
          0.02797425 = score(doc=5288,freq=2.0), product of:
            0.1446067 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041294612 = queryNorm
            0.19345059 = fieldWeight in 5288, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5288)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    Purpose The purpose of this paper is to describe a new method to improve the analysis of search engine results by considering the provider level as well as the domain level. This approach is tested by conducting a study using queries on the topic of insurance comparisons. Design/methodology/approach The authors conducted an empirical study that analyses the results of search queries aimed at comparing insurance companies. The authors used a self-developed software system that automatically queries commercial search engines and automatically extracts the content of the returned result pages for further data analysis. The data analysis was carried out using the KNIME Analytics Platform. Findings Google's top search results are served by only a few providers that frequently appear in these results. The authors show that some providers operate several domains on the same topic and that these domains appear for the same queries in the result lists. Research limitations/implications The authors demonstrate the feasibility of this approach and draw conclusions for further investigations from the empirical study. However, the study is a limited use case based on a limited number of search queries. Originality/value The proposed method allows large-scale analysis of the composition of the top results from commercial search engines. It allows using valid empirical data to determine what users actually see on the search engine result pages.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.3, S.310-324
  15. Sleem-Amer, M.; Bigorgne, I.; Brizard, S.; Santos, L.D.P.D.; Bouhairi, Y. El; Goujon, B.; Lorin, S.; Martineau, C.; Rigouste, L.; Varga, L.: Intelligent semantic search engines for opinion and sentiment mining (2012) 0.03 
    0.03148021 = product of:
  0.06296042 = sum of:
    0.020873476 = weight(_text_:retrieval in 100) [ClassicSimilarity], result of:
      0.020873476 = score(doc=100,freq=2.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.16710453 = fieldWeight in 100, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=100)
    0.021389665 = weight(_text_:use in 100) [ClassicSimilarity], result of:
      0.021389665 = score(doc=100,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.1691581 = fieldWeight in 100, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.0390625 = fieldNorm(doc=100)
    0.009662016 = weight(_text_:of in 100) [ClassicSimilarity], result of:
      0.009662016 = score(doc=100,freq=6.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.1496253 = fieldWeight in 100, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=100)
    0.0110352645 = product of:
      0.022070529 = sum of:
        0.022070529 = weight(_text_:on in 100) [ClassicSimilarity], result of:
          0.022070529 = score(doc=100,freq=8.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.24300331 = fieldWeight in 100, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.0390625 = fieldNorm(doc=100)
      0.5 = coord(1/2)
  0.5 = coord(4/8)
    Abstract
    Over the last years, research and industry players have become increasingly interested in analyzing opinions and sentiments expressed on the social media web for product marketing and business intelligence. In order to adapt to this need search engines not only have to be able to retrieve lists of documents but to directly access, analyze, and interpret topics and opinions. This article covers an intermediate phase of the ongoing industrial research project 'DoXa' aiming at developing a semantic opinion and sentiment mining search engine for the French language. The DoXa search engine enables topic related opinion and sentiment extraction beyond positive and negative polarity using rich linguistic resources. Centering the work on two distinct business use cases, the authors analyze both unstructured Web 2.0 contents (e.g., blogs and forums) and structured questionnaire data sets. The focus is on discovering hidden patterns in the data. To this end, the authors present work in progress on opinion topic relation extraction and visual analytics, linguistic resource construction as well as the combination of OLAP technology with semantic search.
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  16. Johnson, F.; Rowley, J.; Sbaffi, L.: Exploring information interactions in the context of Google (2016) 0.03 
    0.029963072 = product of:
  0.079901524 = sum of:
    0.044457585 = weight(_text_:use in 2885) [ClassicSimilarity], result of:
      0.044457585 = score(doc=2885,freq=6.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.35158852 = fieldWeight in 2885, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=2885)
    0.022201622 = weight(_text_:of in 2885) [ClassicSimilarity], result of:
      0.022201622 = score(doc=2885,freq=22.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.34381276 = fieldWeight in 2885, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=2885)
    0.013242318 = product of:
      0.026484637 = sum of:
        0.026484637 = weight(_text_:on in 2885) [ClassicSimilarity], result of:
          0.026484637 = score(doc=2885,freq=8.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.29160398 = fieldWeight in 2885, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=2885)
      0.5 = coord(1/2)
  0.375 = coord(3/8)
    Abstract
    The study sets out to explore the factors that influence the evaluation of information and the judgments made in the process of finding useful information in web search contexts. Based on a diary study of 2 assigned tasks to search on Google and Google Scholar, factor analysis identified the core constructs of content, relevance, scope, and style, as well as informational and system "ease of use" as influencing the judgment that useful information had been found. Differences were found in the participants' evaluation of information across the search tasks on Google and on Google Scholar when identified by the factors related to both content and ease of use. The findings from this study suggest how searchers might critically evaluate information, and the study identifies a relation between the user's involvement in the information interaction and the influences of the perceived system ease of use and information design.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.4, S.824-840
  17. Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014) 0.03 
    0.028500058 = product of:
  0.076000154 = sum of:
    0.04338471 = weight(_text_:retrieval in 2799) [ClassicSimilarity], result of:
      0.04338471 = score(doc=2799,freq=6.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.34732026 = fieldWeight in 2799, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=2799)
    0.016396983 = weight(_text_:of in 2799) [ClassicSimilarity], result of:
      0.016396983 = score(doc=2799,freq=12.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.25392252 = fieldWeight in 2799, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=2799)
    0.016218461 = product of:
      0.032436922 = sum of:
        0.032436922 = weight(_text_:on in 2799) [ClassicSimilarity], result of:
          0.032436922 = score(doc=2799,freq=12.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.35714048 = fieldWeight in 2799, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=2799)
      0.5 = coord(1/2)
  0.375 = coord(3/8)
    Abstract
    With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  18. What is Schema.org? (2011) 0.03 
    0.02783673 = product of:
  0.07423128 = sum of:
    0.044457585 = weight(_text_:use in 4437) [ClassicSimilarity], result of:
      0.044457585 = score(doc=4437,freq=6.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.35158852 = fieldWeight in 4437, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=4437)
    0.014968331 = weight(_text_:of in 4437) [ClassicSimilarity], result of:
      0.014968331 = score(doc=4437,freq=10.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.23179851 = fieldWeight in 4437, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=4437)
    0.014805362 = product of:
      0.029610723 = sum of:
        0.029610723 = weight(_text_:on in 4437) [ClassicSimilarity], result of:
          0.029610723 = score(doc=4437,freq=10.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.32602316 = fieldWeight in 4437, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=4437)
      0.5 = coord(1/2)
  0.375 = coord(3/8)
    Abstract
    This site provides a collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google and Yahoo! rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Many sites are generated from structured data, which is often stored in databases. When this data is formatted into HTML, it becomes very difficult to recover the original structured data. Many applications, especially search engines, can benefit greatly from direct access to this structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results in order to make it easier for users to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure. A shared markup vocabulary makes easier for webmasters to decide on a markup schema and get the maximum benefit for their efforts. So, in the spirit of sitemaps.org, Bing, Google and Yahoo! have come together to provide a shared collection of schemas that webmasters can use.
  19. Hoeber, O.: Human-centred Web search (2012) 0.03 
    0.027257055 = product of:
  0.07268548 = sum of:
    0.035423465 = weight(_text_:retrieval in 102) [ClassicSimilarity], result of:
      0.035423465 = score(doc=102,freq=4.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.2835858 = fieldWeight in 102, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=102)
    0.025667597 = weight(_text_:use in 102) [ClassicSimilarity], result of:
      0.025667597 = score(doc=102,freq=2.0), product of:
        0.12644777 = queryWeight, product of:
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.041294612 = queryNorm
        0.20298971 = fieldWeight in 102, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0620887 = idf(docFreq=5623, maxDocs=44218)
          0.046875 = fieldNorm(doc=102)
    0.011594418 = weight(_text_:of in 102) [ClassicSimilarity], result of:
      0.011594418 = score(doc=102,freq=6.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.17955035 = fieldWeight in 102, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=102)
  0.375 = coord(3/8)
    Abstract
    People commonly experience difficulties when searching the Web, arising from an incomplete knowledge regarding their information needs, an inability to formulate accurate queries, and a low tolerance for considering the relevance of the search results. While simple and easy to use interfaces have made Web search universally accessible, they provide little assistance for people to overcome the difficulties they experience when their information needs are more complex than simple fact-verification. In human-centred Web search, the purpose of the search engine expands from a simple information retrieval engine to a decision support system. People are empowered to take an active role in the search process, with the search engine supporting them in developing a deeper understanding of their information needs, assisting them in crafting and refining their queries, and aiding them in evaluating and exploring the search results. In this chapter, recent research in this domain is outlined and discussed.
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  20. Ke, W.: Decentralized search and the clustering paradox in large scale information networks (2012) 0.03 
    0.026880767 = product of:
  0.07168204 = sum of:
    0.04338471 = weight(_text_:retrieval in 94) [ClassicSimilarity], result of:
      0.04338471 = score(doc=94,freq=6.0), product of:
        0.124912694 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.041294612 = queryNorm
        0.34732026 = fieldWeight in 94, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=94)
    0.018933605 = weight(_text_:of in 94) [ClassicSimilarity], result of:
      0.018933605 = score(doc=94,freq=16.0), product of:
        0.06457475 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.041294612 = queryNorm
        0.2932045 = fieldWeight in 94, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=94)
    0.009363732 = product of:
      0.018727465 = sum of:
        0.018727465 = weight(_text_:on in 94) [ClassicSimilarity], result of:
          0.018727465 = score(doc=94,freq=4.0), product of:
            0.090823986 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.041294612 = queryNorm
            0.20619515 = fieldWeight in 94, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=94)
      0.5 = coord(1/2)
  0.375 = coord(3/8)
    Abstract
    Amid the rapid growth of information today is the increasing challenge for people to navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web raise important questions about information retrieval in these environments. Collection of all information in advance and centralization of IR operations are extremely difficult, if not impossible, because systems are dynamic and information is distributed. The chapter discusses some of the key issues facing classic information retrieval models and presents a decentralized, organic view of information systems pertaining to search in large scale networks. It focuses on the impact of network structure on search performance and discusses a phenomenon we refer to as the Clustering Paradox, in which the topology of interconnected systems imposes a scalability limit.
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

Authors

Languages

  • e 72
  • d 20

Types

  • a 76
  • el 14
  • m 8
  • s 4
  • r 2
  • x 1
  • More… Less…

Themes

Subjects

Classifications