Search (7 results, page 1 of 1)

0.044248845 = product of:
  0.08849769 = sum of:
    0.08849769 = sum of:
      0.038503684 = weight(_text_:systems in 4888) [ClassicSimilarity], result of:
        0.038503684 = score(doc=4888,freq=4.0), product of:
          0.16037072 = queryWeight, product of:
            3.0731742 = idf(docFreq=5561, maxDocs=44218)
            0.052184064 = queryNorm
          0.24009174 = fieldWeight in 4888, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            3.0731742 = idf(docFreq=5561, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4888)
      0.049994007 = weight(_text_:22 in 4888) [ClassicSimilarity], result of:
        0.049994007 = score(doc=4888,freq=4.0), product of:
          0.1827397 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.052184064 = queryNorm
          0.27358043 = fieldWeight in 4888, 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=4888)
  0.5 = coord(1/2)

Abstract

This paper centres on the tools for the management of new digital documents, which are not only textual, but also visual-video, audio or multimedia in the full sense. Among the aims is to demonstrate that operating within the terms of generic Information Retrieval through textual language only is limiting, and it is instead necessary to consider ampler criteria, such as those of MultiMedia Information Retrieval, according to which, every type of digital document can be analyzed and searched by the proper elements of language for its proper nature. MMIR is presented as the organic complex of the systems of Text Retrieval, Visual Retrieval, Video Retrieval, and Audio Retrieval, each of which has an approach to information management that handles the concrete textual, visual, audio, or video content of the documents directly, here defined as content-based. In conclusion, the limits of this content-based objective access to documents is underlined. The discrepancy known as the semantic gap is that which occurs between semantic-interpretive access and content-based access. Finally, the integration of these conceptions is explained, gathering and composing the merits and the advantages of each of the approaches and of the systems to access to information.

Date

22. 1.2012 13:02:10

Source

Knowledge organization. 39(2012) no.1, S.13-22

0.013613109 = product of:
  0.027226217 = sum of:
    0.027226217 = product of:
      0.054452434 = sum of:
        0.054452434 = weight(_text_:systems in 3584) [ClassicSimilarity], result of:
          0.054452434 = score(doc=3584,freq=8.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.339541 = fieldWeight in 3584, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3584)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Emotional meaning is critical for users to retrieve relevant images. However, because emotional meanings are subject to the individual viewer's interpretation, they are considered difficult to implement when designing image retrieval systems. With the intent of making an image's emotional messages more readily accessible, this study aims to test a new approach designed to enhance the accessibility of emotional meanings during the image search process. This approach utilizes image searchers' emotional reactions, which are quantitatively measured. Broadly used quantitative measurements for emotional reactions, Semantic Differential (SD) and Self-Assessment Manikin (SAM), were selected as tools for gathering users' reactions. Emotional representations obtained from these two tools were compared with three image perception tasks: searching, describing, and sorting. A survey questionnaire with a set of 12 images was administered to 58 participants, which were tagged with basic emotions. Results demonstrated that the SAM represents basic emotions on 2-dimensional plots (pleasure and arousal dimensions), and this representation consistently corresponded to the three image perception tasks. This study provided experimental evidence that quantitative users' reactions can be a useful complementary element of current image retrieval/indexing systems. Integrating users' reactions obtained from the SAM into image browsing systems would reduce the efforts of human indexers as well as improve the effectiveness of image retrieval systems.

0.013476291 = product of:
  0.026952581 = sum of:
    0.026952581 = product of:
      0.053905163 = sum of:
        0.053905163 = weight(_text_:systems in 5139) [ClassicSimilarity], result of:
          0.053905163 = score(doc=5139,freq=4.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.33612844 = fieldWeight in 5139, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5139)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The article is an introduction to the development of Andersen's concept of textual tools used in knowledge organization (KO) in light of the theory of genres and activity systems. In particular, the question is based on the concepts of genre connectivity and genre group, in addition to previously established concepts such as genre hierarchy, set, system, and repertoire. Five genre groups used in KO are described. The analysis of groups, systems, and selected genres used in KO is provided, based on the method proposed by Yates and Orlikowski. The aim is to show the genre system as a part of the activity system, and thus as a framework for KO.

0.010605331 = product of:
  0.021210661 = sum of:
    0.021210661 = product of:
      0.042421322 = sum of:
        0.042421322 = weight(_text_:22 in 1416) [ClassicSimilarity], result of:
          0.042421322 = score(doc=1416,freq=2.0), product of:
            0.1827397 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.052184064 = queryNorm
            0.23214069 = fieldWeight in 1416, 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=1416)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

0.0094314385 = product of:
  0.018862877 = sum of:
    0.018862877 = product of:
      0.037725754 = sum of:
        0.037725754 = weight(_text_:systems in 2671) [ClassicSimilarity], result of:
          0.037725754 = score(doc=2671,freq=6.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.2352409 = fieldWeight in 2671, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.03125 = fieldNorm(doc=2671)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.

0.008167865 = product of:
  0.01633573 = sum of:
    0.01633573 = product of:
      0.03267146 = sum of:
        0.03267146 = weight(_text_:systems in 3953) [ClassicSimilarity], result of:
          0.03267146 = score(doc=3953,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.2037246 = fieldWeight in 3953, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.046875 = fieldNorm(doc=3953)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - This paper endeavours to show the possibilities for thematic description of audio-visual documents for television with the aim of promoting and facilitating information retrieval. Design/methodology/approach - To achieve these goals different database fields are shown, as well as the way in which they are organised for indexing and thematic element description, analysed and used as an example. Some of the database fields are extracted from an analytical study of the documentary system of television in Spain. Others are being tested in university television on which indexing experiments are carried out. Findings - Not all thematic descriptions are used on television information systems; nevertheless, some television channels do use thematic descriptions of both image and sound, applying thesauri. Moreover, it is possible to access sequences using full text retrieval as well. Originality/value - The development of the documentary task, applying the described techniques, promotes thematic indexing and hence thematic retrieval. Given the fact that this is without doubt one of the aspects most demanded by television journalists (along with people's names). This conceptualisation translates into the adaptation of databases to new indexing methods.

0.008167865 = product of:
  0.01633573 = sum of:
    0.01633573 = product of:
      0.03267146 = sum of:
        0.03267146 = weight(_text_:systems in 299) [ClassicSimilarity], result of:
          0.03267146 = score(doc=299,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.2037246 = fieldWeight in 299, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.046875 = fieldNorm(doc=299)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - The paper aims to explain the character and causes of obsolescence in assigned subject descriptors. Design/methodology/approach - The paper takes the form of a conceptual analysis with examples and reference to existing literature. Findings - Subject description comes in two forms: assigning the name or code of a subject to a document and assigning a document to a named subject category. Each method associates a document with the name of a subject. This naming activity is the site of tensions between the procedural need of information systems for stable records and the inherent multiplicity and instability of linguistic expressions. As languages change, previously assigned subject descriptions become obsolescent. The issues, tensions, and compromises involved are introduced. Originality/value - Drawing on the work of Robert Fairthorne and others, an explanation of the unavoidable obsolescence of assigned subject headings is presented. The discussion relates to libraries, but the same issues arise in any context in which subject description is expected to remain useful for an extended period of time.