Search (2423 results, page 1 of 122)

  • × year_i:[2000 TO 2010}
  1. Roto, V.: Search on mobile phones. (2006) 0.11
    0.10669871 = product of:
      0.21339741 = sum of:
        0.21339741 = sum of:
          0.15703757 = weight(_text_:search in 5304) [ClassicSimilarity], result of:
            0.15703757 = score(doc=5304,freq=16.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.86891925 = fieldWeight in 5304, product of:
                4.0 = tf(freq=16.0), with freq of:
                  16.0 = termFreq=16.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0625 = fieldNorm(doc=5304)
          0.056359846 = weight(_text_:22 in 5304) [ClassicSimilarity], result of:
            0.056359846 = score(doc=5304,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.30952093 = fieldWeight in 5304, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0625 = fieldNorm(doc=5304)
      0.5 = coord(1/2)
    
    Abstract
    The search tools familiar from the personal computer are propagating to mobile devices. Are users willing to type keywords with the limited keypad of an ordinary mobile phone? How does mobile search differ from stationary search? The author found that users are surprisingly willing to use search also with the traditional phone keypad, and foresees a search revolution as mobile devices enable location-based search.
    Date
    22. 7.2006 18:35:39
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  2. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.10
    0.103721194 = sum of:
      0.08258625 = product of:
        0.24775875 = sum of:
          0.24775875 = weight(_text_:3a in 562) [ClassicSimilarity], result of:
            0.24775875 = score(doc=562,freq=2.0), product of:
              0.4408377 = queryWeight, product of:
                8.478011 = idf(docFreq=24, maxDocs=44218)
                0.051997773 = queryNorm
              0.56201804 = fieldWeight in 562, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                8.478011 = idf(docFreq=24, maxDocs=44218)
                0.046875 = fieldNorm(doc=562)
        0.33333334 = coord(1/3)
      0.02113494 = product of:
        0.04226988 = sum of:
          0.04226988 = weight(_text_:22 in 562) [ClassicSimilarity], result of:
            0.04226988 = score(doc=562,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 562, 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=562)
        0.5 = coord(1/2)
    
    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  3. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.10
    0.09789589 = product of:
      0.19579178 = sum of:
        0.19579178 = sum of:
          0.097162046 = weight(_text_:search in 3445) [ClassicSimilarity], result of:
            0.097162046 = score(doc=3445,freq=2.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.5376164 = fieldWeight in 3445, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.109375 = fieldNorm(doc=3445)
          0.09862973 = weight(_text_:22 in 3445) [ClassicSimilarity], result of:
            0.09862973 = score(doc=3445,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.5416616 = fieldWeight in 3445, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.109375 = fieldNorm(doc=3445)
      0.5 = coord(1/2)
    
    Date
    25. 8.2005 17:42:22
  4. Wildemuth, B.M.: Evidence-based practice in search interface design (2006) 0.09
    0.08892408 = product of:
      0.17784816 = sum of:
        0.17784816 = sum of:
          0.1285333 = weight(_text_:search in 5302) [ClassicSimilarity], result of:
            0.1285333 = score(doc=5302,freq=14.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.71119964 = fieldWeight in 5302, product of:
                3.7416575 = tf(freq=14.0), with freq of:
                  14.0 = termFreq=14.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5302)
          0.049314864 = weight(_text_:22 in 5302) [ClassicSimilarity], result of:
            0.049314864 = score(doc=5302,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.2708308 = fieldWeight in 5302, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5302)
      0.5 = coord(1/2)
    
    Abstract
    An evidence-based practice approach to search interface design is proposed, with the goal of designing interfaces that adequately support search strategy formulation and reformulation. Relevant findings from studies of information professionals' searching behaviors, end users' searching of bibliographic databases, and search behaviors on the Web are highlighted. Three brief examples are presented to illustrate the ways in which findings from such studies can be used to make decisions about the design of search interfaces. If academic research can be effectively connected with design practice, we can discover which design practices truly are best practices and incorporate them into future search interfaces.
    Date
    22. 7.2006 18:30:09
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  5. Vaughan, M.W.; Resnick, M.L.: Search user interfaces : best practices and future visions (2006) 0.08
    0.08429915 = product of:
      0.1685983 = sum of:
        0.1685983 = sum of:
          0.09814849 = weight(_text_:search in 5191) [ClassicSimilarity], result of:
            0.09814849 = score(doc=5191,freq=4.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.54307455 = fieldWeight in 5191, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.078125 = fieldNorm(doc=5191)
          0.07044981 = weight(_text_:22 in 5191) [ClassicSimilarity], result of:
            0.07044981 = score(doc=5191,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.38690117 = fieldWeight in 5191, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.078125 = fieldNorm(doc=5191)
      0.5 = coord(1/2)
    
    Date
    22. 7.2006 17:37:31
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  6. Rose, D.E.: Reconciling information-seeking behavior with search user interfaces for the Web (2006) 0.08
    0.08415678 = product of:
      0.16831356 = sum of:
        0.16831356 = sum of:
          0.11899871 = weight(_text_:search in 5296) [ClassicSimilarity], result of:
            0.11899871 = score(doc=5296,freq=12.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.65844285 = fieldWeight in 5296, product of:
                3.4641016 = tf(freq=12.0), with freq of:
                  12.0 = termFreq=12.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5296)
          0.049314864 = weight(_text_:22 in 5296) [ClassicSimilarity], result of:
            0.049314864 = score(doc=5296,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.2708308 = fieldWeight in 5296, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5296)
      0.5 = coord(1/2)
    
    Abstract
    User interfaces of Web search engines reflect attributes of the underlying tools used to create them, rather than what we know about how people look for information. In this article, the author examines several characteristics of user search behavior: the variety of information-seeking goals, the cultural and situational context of search, and the iterative nature of the search task. An analysis of these characteristics suggests ways that interfaces can be redesigned to make searching more effective for users.
    Date
    22. 7.2006 17:58:06
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  7. Hendry, D.G.: Workspaces for search (2006) 0.08
    0.08415678 = product of:
      0.16831356 = sum of:
        0.16831356 = sum of:
          0.11899871 = weight(_text_:search in 5297) [ClassicSimilarity], result of:
            0.11899871 = score(doc=5297,freq=12.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.65844285 = fieldWeight in 5297, product of:
                3.4641016 = tf(freq=12.0), with freq of:
                  12.0 = termFreq=12.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5297)
          0.049314864 = weight(_text_:22 in 5297) [ClassicSimilarity], result of:
            0.049314864 = score(doc=5297,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.2708308 = fieldWeight in 5297, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5297)
      0.5 = coord(1/2)
    
    Abstract
    Progress in search interfaces requires vigorous inquiry into how search features can be embedded into application environments such as those for decision-making, personal information collecting, and designing. Progress can be made by focusing on mid-level descriptions of how search components can draw upon and update workspace content and structure. The immediate goal is to advance our understanding of how to shape and exploit context in search. The long-term goal is to develop an interdisciplinary design resource that enables stakeholders in the computing, social, and information sciences to more richly impact each others' work.
    Date
    22. 7.2006 18:01:11
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  8. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.08
    0.07694328 = product of:
      0.15388656 = sum of:
        0.15388656 = sum of:
          0.0841448 = weight(_text_:search in 5295) [ClassicSimilarity], result of:
            0.0841448 = score(doc=5295,freq=6.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.46558946 = fieldWeight in 5295, product of:
                2.4494898 = tf(freq=6.0), with freq of:
                  6.0 = termFreq=6.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5295)
          0.069741756 = weight(_text_:22 in 5295) [ClassicSimilarity], result of:
            0.069741756 = score(doc=5295,freq=4.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.38301262 = fieldWeight in 5295, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5295)
      0.5 = coord(1/2)
    
    Abstract
    A new search paradigm, in which the primary user activity is the guided exploration of a complex information space rather than the retrieval of items based on precise specifications, is proposed. The author claims that this paradigm is the norm in most practical applications, and that solutions based on traditional search methods are not effective in this context. He then presents a solution based on dynamic taxonomies, a knowledge management model that effectively guides users to reach their goal while giving them total freedom in exploring the information base. Applications, benefits, and current research are discussed.
    Date
    22. 7.2006 17:56:22
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  9. Davis, L.: Designing a search user interface for a digital library (2006) 0.08
    0.07626267 = product of:
      0.15252534 = sum of:
        0.15252534 = sum of:
          0.096165486 = weight(_text_:search in 5294) [ClassicSimilarity], result of:
            0.096165486 = score(doc=5294,freq=6.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.5321022 = fieldWeight in 5294, product of:
                2.4494898 = tf(freq=6.0), with freq of:
                  6.0 = termFreq=6.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0625 = fieldNorm(doc=5294)
          0.056359846 = weight(_text_:22 in 5294) [ClassicSimilarity], result of:
            0.056359846 = score(doc=5294,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.30952093 = fieldWeight in 5294, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0625 = fieldNorm(doc=5294)
      0.5 = coord(1/2)
    
    Abstract
    The author describes some of the challenges, decisions, and processes that affected the design and development of the search user interface for Version 2 of the Digital Library for Earth System Education (DLESE; www.dlese.org), released July 29, 2003. The DLESE is a community-led effort funded by the National Science Foundation and is part of the National Science Digital Library (NSDL).
    Date
    22. 7.2006 17:48:54
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  10. Gremett, P.: Utilizing a user's context to improve search results (2006) 0.08
    0.07626267 = product of:
      0.15252534 = sum of:
        0.15252534 = sum of:
          0.096165486 = weight(_text_:search in 5299) [ClassicSimilarity], result of:
            0.096165486 = score(doc=5299,freq=6.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.5321022 = fieldWeight in 5299, product of:
                2.4494898 = tf(freq=6.0), with freq of:
                  6.0 = termFreq=6.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0625 = fieldNorm(doc=5299)
          0.056359846 = weight(_text_:22 in 5299) [ClassicSimilarity], result of:
            0.056359846 = score(doc=5299,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.30952093 = fieldWeight in 5299, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0625 = fieldNorm(doc=5299)
      0.5 = coord(1/2)
    
    Abstract
    Usability evaluations and observations of users shopping at Amazon.com (http://www.amazon.com) revealed some interesting user behaviors. The mixed behavior patterns were leveraged to create an interface for an e-commerce product. The author describes some design practices for providing a scoped search interface for an e-commerce site.
    Date
    22. 7.2006 18:17:44
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  11. Resnick, M.L.; Vaughan, M.W.: Best practices and future visions for search user interfaces (2006) 0.08
    0.07622065 = product of:
      0.1524413 = sum of:
        0.1524413 = sum of:
          0.110171415 = weight(_text_:search in 5293) [ClassicSimilarity], result of:
            0.110171415 = score(doc=5293,freq=14.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.6095997 = fieldWeight in 5293, product of:
                3.7416575 = tf(freq=14.0), with freq of:
                  14.0 = termFreq=14.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.046875 = fieldNorm(doc=5293)
          0.04226988 = weight(_text_:22 in 5293) [ClassicSimilarity], result of:
            0.04226988 = score(doc=5293,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 5293, 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=5293)
      0.5 = coord(1/2)
    
    Abstract
    The authors describe a set of best practices that were developed to assist in the design of search user interfaces. Search user interfaces represent a challenging design domain because novices who have no desire to learn the mechanics of search engine architecture or algorithms often use them. These can lead to frustration and task failure when it is not addressed by the user interface. The best practices are organized into five domains: the corpus, search algorithms, user and task context, the search interface, and mobility. In each section the authors present an introduction to the design challenges related to the domain and a set of best practices for creating a user interface that facilitates effective use by a broad population of users and tasks.
    Date
    22. 7.2006 17:38:51
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  12. Komlodi, A.; Soergel, D.; Marchionini, G.: Search histories for user support in user interfaces (2006) 0.08
    0.07622065 = product of:
      0.1524413 = sum of:
        0.1524413 = sum of:
          0.110171415 = weight(_text_:search in 5298) [ClassicSimilarity], result of:
            0.110171415 = score(doc=5298,freq=14.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.6095997 = fieldWeight in 5298, product of:
                3.7416575 = tf(freq=14.0), with freq of:
                  14.0 = termFreq=14.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.046875 = fieldNorm(doc=5298)
          0.04226988 = weight(_text_:22 in 5298) [ClassicSimilarity], result of:
            0.04226988 = score(doc=5298,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 5298, 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=5298)
      0.5 = coord(1/2)
    
    Abstract
    The authors describe user interface tools based on search histories to support legal information seekers. The design of the tools was informed by the results of a user study (Komlodi, 2002a) that examined the use of human memory, external memory aids, and search histories in legal information seeking and derived interface design recommendations for information storage and retrieval systems. The data collected were analyzed to identify potential task areas where search histories can support information seeking and use. The results show that many information-seeking tasks can take advantage of automatically and manually recorded history information. These findings encouraged the design of user interface tools building on search history information: direct search history displays, history-enabled scratchpad facilities, and organized results collection tools.
    Date
    22. 7.2006 18:04:19
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  13. Morrison, P.J.: Tagging and searching : search retrieval effectiveness of folksonomies on the World Wide Web (2008) 0.08
    0.07622065 = product of:
      0.1524413 = sum of:
        0.1524413 = sum of:
          0.110171415 = weight(_text_:search in 2109) [ClassicSimilarity], result of:
            0.110171415 = score(doc=2109,freq=14.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.6095997 = fieldWeight in 2109, product of:
                3.7416575 = tf(freq=14.0), with freq of:
                  14.0 = termFreq=14.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.046875 = fieldNorm(doc=2109)
          0.04226988 = weight(_text_:22 in 2109) [ClassicSimilarity], result of:
            0.04226988 = score(doc=2109,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 2109, 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=2109)
      0.5 = coord(1/2)
    
    Abstract
    Many Web sites have begun allowing users to submit items to a collection and tag them with keywords. The folksonomies built from these tags are an interesting topic that has seen little empirical research. This study compared the search information retrieval (IR) performance of folksonomies from social bookmarking Web sites against search engines and subject directories. Thirty-four participants created 103 queries for various information needs. Results from each IR system were collected and participants judged relevance. Folksonomy search results overlapped with those from the other systems, and documents found by both search engines and folksonomies were significantly more likely to be judged relevant than those returned by any single IR system type. The search engines in the study had the highest precision and recall, but the folksonomies fared surprisingly well. Del.icio.us was statistically indistinguishable from the directories in many cases. Overall the directories were more precise than the folksonomies but they had similar recall scores. Better query handling may enhance folksonomy IR performance further. The folksonomies studied were promising, and may be able to improve Web search performance.
    Date
    1. 8.2008 12:39:22
  14. Jones, M.; Buchanan, G.; Cheng, T.-C.; Jain, P.: Changing the pace of search : supporting background information seeking (2006) 0.07
    0.073238455 = product of:
      0.14647691 = sum of:
        0.14647691 = sum of:
          0.097162046 = weight(_text_:search in 5287) [ClassicSimilarity], result of:
            0.097162046 = score(doc=5287,freq=8.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.5376164 = fieldWeight in 5287, product of:
                2.828427 = tf(freq=8.0), with freq of:
                  8.0 = termFreq=8.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5287)
          0.049314864 = weight(_text_:22 in 5287) [ClassicSimilarity], result of:
            0.049314864 = score(doc=5287,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.2708308 = fieldWeight in 5287, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=5287)
      0.5 = coord(1/2)
    
    Abstract
    Almost all Web searches are carried out while the user is sitting at a conventional desktop computer connected to the Internet. Although online, handheld, mobile search offers new possibilities, the fast-paced, focused style of interaction may not be appropriate for all user search needs. The authors explore an alternative, relaxed style for Web searching that asynchronously combines an offline handheld computer and an online desktop personal computer. They discuss the role and utility of such an approach, present a tool to meet these user needs, and discuss its relation to other systems.
    Date
    22. 7.2006 18:37:49
    Footnote
    Beitrag in einer Special Section "Perspectives on Search User Interfaces: Best Practices and Future Visions"
  15. Su, L.T.: ¬A comprehensive and systematic model of user evaluation of Web search engines : Il. An evaluation by undergraduates (2003) 0.07
    0.07247912 = product of:
      0.14495824 = sum of:
        0.14495824 = sum of:
          0.109733336 = weight(_text_:search in 2117) [ClassicSimilarity], result of:
            0.109733336 = score(doc=2117,freq=20.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.60717577 = fieldWeight in 2117, product of:
                4.472136 = tf(freq=20.0), with freq of:
                  20.0 = termFreq=20.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0390625 = fieldNorm(doc=2117)
          0.035224903 = weight(_text_:22 in 2117) [ClassicSimilarity], result of:
            0.035224903 = score(doc=2117,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.19345059 = fieldWeight in 2117, 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=2117)
      0.5 = coord(1/2)
    
    Abstract
    This paper presents an application of the model described in Part I to the evaluation of Web search engines by undergraduates. The study observed how 36 undergraduate used four major search engines to find information for their own individual problems and how they evaluated these engines based an actual interaction with the search engines. User evaluation was based an 16 performance measures representing five evaluation criteria: relevance, efficiency, utility, user satisfaction, and connectivity. Non-performance (user-related) measures were also applied. Each participant searched his/ her own topic an all four engines and provided satisfaction ratings for system features and interaction and reasons for satisfaction. Each also made relevance judgements of retrieved items in relation to his/her own information need and participated in post-search Interviews to provide reactions to the search results and overall performance. The study found significant differences in precision PR1 relative recall, user satisfaction with output display, time saving, value of search results, and overall performance among the four engines and also significant engine by discipline interactions an all these measures. In addition, the study found significant differences in user satisfaction with response time among four engines, and significant engine by discipline interaction in user satisfaction with search interface. None of the four search engines dominated in every aspect of the multidimensional evaluation. Content analysis of verbal data identified a number of user criteria and users evaluative comments based an these criteria. Results from both quantitative analysis and content analysis provide insight for system design and development, and useful feedback an strengths and weaknesses of search engines for system improvement
    Date
    24. 1.2004 18:27:22
  16. Bilal, D.: Children's use of the Yahooligans! Web search engine : III. Cognitive and physical behaviors on fully self-generated search tasks (2002) 0.07
    0.07213438 = product of:
      0.14426877 = sum of:
        0.14426877 = sum of:
          0.10199889 = weight(_text_:search in 5228) [ClassicSimilarity], result of:
            0.10199889 = score(doc=5228,freq=12.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.5643796 = fieldWeight in 5228, product of:
                3.4641016 = tf(freq=12.0), with freq of:
                  12.0 = termFreq=12.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.046875 = fieldNorm(doc=5228)
          0.04226988 = weight(_text_:22 in 5228) [ClassicSimilarity], result of:
            0.04226988 = score(doc=5228,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 5228, 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=5228)
      0.5 = coord(1/2)
    
    Abstract
    Bilal, in this third part of her Yahooligans! study looks at children's performance with self-generated search tasks, as compared to previously assigned search tasks looking for differences in success, cognitive behavior, physical behavior, and task preference. Lotus ScreenCam was used to record interactions and post search interviews to record impressions. The subjects, the same 22 seventh grade children in the previous studies, generated topics of interest that were mediated with the researcher into more specific topics where necessary. Fifteen usable sessions form the basis of the study. Eleven children were successful in finding information, a rate of 73% compared to 69% in assigned research questions, and 50% in assigned fact-finding questions. Eighty-seven percent began using one or two keyword searches. Spelling was a problem. Successful children made fewer keyword searches and the number of search moves averaged 5.5 as compared to 2.4 on the research oriented task and 3.49 on the factual. Backtracking and looping were common. The self-generated task was preferred by 47% of the subjects.
  17. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.07
    0.06929502 = product of:
      0.13859004 = sum of:
        0.13859004 = sum of:
          0.1139326 = weight(_text_:search in 2509) [ClassicSimilarity], result of:
            0.1139326 = score(doc=2509,freq=44.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.6304111 = fieldWeight in 2509, product of:
                6.6332498 = tf(freq=44.0), with freq of:
                  44.0 = termFreq=44.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.02734375 = fieldNorm(doc=2509)
          0.024657432 = weight(_text_:22 in 2509) [ClassicSimilarity], result of:
            0.024657432 = score(doc=2509,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.1354154 = fieldWeight in 2509, 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=2509)
      0.5 = coord(1/2)
    
    Abstract
    A relevancy-ranking algorithm for a natural language interface to Boolean online public access catalogs (OPACs) was formulated and compared with that currently used in a knowledge-based search interface called the E-Referencer, being developed by the authors. The algorithm makes use of seven weIl-known ranking criteria: breadth of match, section weighting, proximity of query words, variant word forms (stemming), document frequency, term frequency and document length. The algorithm converts a natural language query into a series of increasingly broader Boolean search statements. In a small experiment with ten subjects in which the algorithm was simulated by hand, the algorithm obtained good results with a mean overall precision of 0.42 and mean average precision of 0.62, representing a 27 percent improvement in precision and 41 percent improvement in average precision compared to the E-Referencer. The usefulness of each step in the algorithm was analyzed and suggestions are made for improving the algorithm.
    Content
    "Most Web search engines accept natural language queries, perform some kind of fuzzy matching and produce ranked output, displaying first the documents that are most likely to be relevant. On the other hand, most library online public access catalogs (OPACs) an the Web are still Boolean retrieval systems that perform exact matching, and require users to express their search requests precisely in a Boolean search language and to refine their search statements to improve the search results. It is well-documented that users have difficulty searching Boolean OPACs effectively (e.g. Borgman, 1996; Ensor, 1992; Wallace, 1993). One approach to making OPACs easier to use is to develop a natural language search interface that acts as a middleware between the user's Web browser and the OPAC system. The search interface can accept a natural language query from the user and reformulate it as a series of Boolean search statements that are then submitted to the OPAC. The records retrieved by the OPAC are ranked by the search interface before forwarding them to the user's Web browser. The user, then, does not need to interact directly with the Boolean OPAC but with the natural language search interface or search intermediary. The search interface interacts with the OPAC system an the user's behalf. The advantage of this approach is that no modification to the OPAC or library system is required. Furthermore, the search interface can access multiple OPACs, acting as a meta search engine, and integrate search results from various OPACs before sending them to the user. The search interface needs to incorporate a method for converting the user's natural language query into a series of Boolean search statements, and for ranking the OPAC records retrieved. The purpose of this study was to develop a relevancyranking algorithm for a search interface to Boolean OPAC systems. This is part of an on-going effort to develop a knowledge-based search interface to OPACs called the E-Referencer (Khoo et al., 1998, 1999; Poo et al., 2000). E-Referencer v. 2 that has been implemented applies a repertoire of initial search strategies and reformulation strategies to retrieve records from OPACs using the Z39.50 protocol, and also assists users in mapping query keywords to the Library of Congress subject headings."
    Source
    Electronic library. 22(2004) no.2, S.112-120
  18. Avrahami, T.T.; Yau, L.; Si, L.; Callan, J.P.: ¬The FedLemur project : Federated search in the real world (2006) 0.07
    0.06769086 = product of:
      0.13538171 = sum of:
        0.13538171 = sum of:
          0.09311183 = weight(_text_:search in 5271) [ClassicSimilarity], result of:
            0.09311183 = score(doc=5271,freq=10.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.51520574 = fieldWeight in 5271, product of:
                3.1622777 = tf(freq=10.0), with freq of:
                  10.0 = termFreq=10.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.046875 = fieldNorm(doc=5271)
          0.04226988 = weight(_text_:22 in 5271) [ClassicSimilarity], result of:
            0.04226988 = score(doc=5271,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 5271, 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=5271)
      0.5 = coord(1/2)
    
    Abstract
    Federated search and distributed information retrieval systems provide a single user interface for searching multiple full-text search engines. They have been an active area of research for more than a decade, but in spite of their success as a research topic, they are still rare in operational environments. This article discusses a prototype federated search system developed for the U.S. government's FedStats Web portal, and the issues addressed in adapting research solutions to this operational environment. A series of experiments explore how well prior research results, parameter settings, and heuristics apply in the FedStats environment. The article concludes with a set of lessons learned from this technology transfer effort, including observations about search engine quality in the real world.
    Date
    22. 7.2006 16:02:07
  19. Nicholson, S.; Sierra, T.; Eseryel, U.Y.; Park, J.-H.; Barkow, P.; Pozo, E.J.; Ward, J.: How much of it is real? : analysis of paid placement in Web search engine results (2006) 0.07
    0.06769086 = product of:
      0.13538171 = sum of:
        0.13538171 = sum of:
          0.09311183 = weight(_text_:search in 5278) [ClassicSimilarity], result of:
            0.09311183 = score(doc=5278,freq=10.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.51520574 = fieldWeight in 5278, product of:
                3.1622777 = tf(freq=10.0), with freq of:
                  10.0 = termFreq=10.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.046875 = fieldNorm(doc=5278)
          0.04226988 = weight(_text_:22 in 5278) [ClassicSimilarity], result of:
            0.04226988 = score(doc=5278,freq=2.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.23214069 = fieldWeight in 5278, 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=5278)
      0.5 = coord(1/2)
    
    Abstract
    Most Web search tools integrate sponsored results with results from their internal editorial database in providing results to users. The goal of this research is to get a better idea of how much of the screen real estate displays real editorial results as compared to sponsored results. The overall average results are that 40% of all results presented on the first screen are real results, and when the entire first Web page is considered, 67% of the results are nonsponsored results. For general search tools such as Google, 56% of the first screen and 82% of the first Web page contain nonsponsored results. Other results include that query structure makes a significant difference in the percentage of nonsponsored results returned by a search. Similarly, the topic of the query also can have a significant effect on the percentage of sponsored results displayed by most Web search tools.
    Date
    22. 7.2006 16:32:57
  20. Pennanen, M.; Vakkari, P.: Students' conceptual structure, search process, and outcome while preparing a research proposal : a longitudinal case study (2003) 0.07
    0.06740731 = product of:
      0.13481462 = sum of:
        0.13481462 = sum of:
          0.084999084 = weight(_text_:search in 1682) [ClassicSimilarity], result of:
            0.084999084 = score(doc=1682,freq=12.0), product of:
              0.18072747 = queryWeight, product of:
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.051997773 = queryNorm
              0.47031635 = fieldWeight in 1682, product of:
                3.4641016 = tf(freq=12.0), with freq of:
                  12.0 = termFreq=12.0
                3.475677 = idf(docFreq=3718, maxDocs=44218)
                0.0390625 = fieldNorm(doc=1682)
          0.049815536 = weight(_text_:22 in 1682) [ClassicSimilarity], result of:
            0.049815536 = score(doc=1682,freq=4.0), product of:
              0.18208735 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051997773 = queryNorm
              0.27358043 = fieldWeight in 1682, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0390625 = fieldNorm(doc=1682)
      0.5 = coord(1/2)
    
    Abstract
    This article focuses an analysing students' information needs in terms of conceptual understanding of the topic they propose to study and its consequences for the search process and outcome. The research subjects were 22 undergraduates of psychology attending a seminar for preparing a research proposal for a small empirical study. They were asked to make searches in the PsycINFO database for their task in the beginning and end of the seminar. A pre- and postsearch interview was conducted in both sessions. The students were asked to think aloud in the sessions. This was recorded, as were the transaction logs. The results show that during the preparation of research proposals different features of the students' conceptual structure were connected to the search success. Students' ability to cover their conceptual construct by query terms was the major feature affecting search success during the whole process. In the beginning also the number of concepts and the proportion of subconcepts in the construct contributed indirectly via search tactics to retrieving partly useful references. Students' ability to extract new query terms from retrieved items improved search results.
    Date
    19. 6.2003 17:22:33

Languages

Types

  • a 2061
  • m 223
  • el 176
  • s 78
  • b 28
  • x 19
  • i 10
  • r 6
  • n 4
  • p 1
  • More… Less…

Themes

Subjects

Classifications