Search (8 results, page 1 of 1)

0.01442888 = product of:
  0.02885776 = sum of:
    0.02885776 = product of:
      0.05771552 = sum of:
        0.05771552 = weight(_text_:work in 5640) [ClassicSimilarity], result of:
          0.05771552 = score(doc=5640,freq=4.0), product of:
            0.20127523 = queryWeight, product of:
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.054837555 = queryNorm
            0.28674924 = fieldWeight in 5640, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5640)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Aboutness ranks amongst our field's greatest bugbears. What is a work about? How can this be known? This mirrors debates within the philosophy of language, where the concept of representation has similarly evaded satisfactory definition. This paper proposes that we abandon the strong sense of the word aboutness, which seems to promise some inherent relationship between work and subject, or, in philosophical terms, between word and world. Instead, we seek an etymological reset to the older sense of aboutness as "in the vicinity, nearby; in some place or various places nearby; all over a surface." To distinguish this sense in the context of information studies, we introduce the term episemantics. The authors have each independently applied this term in slightly different contexts and scales (Hauser 2018a; Tennis 2016), and this article presents a unified definition of the term and guidelines for applying it at the scale of both words and works. The resulting weak concept of aboutness is pragmatic, in Star's sense of a focus on consequences over antecedents, while reserving space for the critique and improvement of aboutness determinations within various contexts and research programs. The paper finishes with a discussion of the implication of the concept of episemantics and methodological possibilities it offers for knowledge organization research and practice. We draw inspiration from Melvil Dewey's use of physical aroundness in his first classification system and ask how aroundness might be more effectively operationalized in digital environments.

0.014283863 = product of:
  0.028567726 = sum of:
    0.028567726 = product of:
      0.05713545 = sum of:
        0.05713545 = weight(_text_:work in 5170) [ClassicSimilarity], result of:
          0.05713545 = score(doc=5170,freq=2.0), product of:
            0.20127523 = queryWeight, product of:
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.054837555 = queryNorm
            0.28386727 = fieldWeight in 5170, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5170)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Catalogers' judgment has been frequently mentioned, but rarely has been researched in formal studies. The purpose of this article is to investigate catalogers' judgment through an exploration of the texts collected in the database of Library and Information Science Source. Verbs, adjectives, and nouns intimately associated with catalogers' judgment were extracted, analyzed, and grouped into 16 categories, which lead to 5 conceptual descriptions. The results of this study provide cataloging professionals with an overall picture on aspects of catalogers' judgment, which may help library school students and graduates and novice catalogers to become independent and confident decision makers relating to cataloging work.

0.013134033 = product of:
  0.026268067 = sum of:
    0.026268067 = product of:
      0.052536134 = sum of:
        0.052536134 = weight(_text_:22 in 4888) [ClassicSimilarity], result of:
          0.052536134 = score(doc=4888,freq=4.0), product of:
            0.19203177 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.054837555 = 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)
  0.5 = coord(1/2)

Date

22. 1.2012 13:02:10

Source

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

0.012243311 = product of:
  0.024486622 = sum of:
    0.024486622 = product of:
      0.048973244 = sum of:
        0.048973244 = weight(_text_:work in 299) [ClassicSimilarity], result of:
          0.048973244 = score(doc=299,freq=2.0), product of:
            0.20127523 = queryWeight, product of:
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.054837555 = queryNorm
            0.2433148 = fieldWeight in 299, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6703904 = idf(docFreq=3060, 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.

0.011144597 = product of:
  0.022289194 = sum of:
    0.022289194 = product of:
      0.04457839 = sum of:
        0.04457839 = weight(_text_:22 in 1416) [ClassicSimilarity], result of:
          0.04457839 = score(doc=1416,freq=2.0), product of:
            0.19203177 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.054837555 = 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

0.010202759 = product of:
  0.020405518 = sum of:
    0.020405518 = product of:
      0.040811036 = sum of:
        0.040811036 = weight(_text_:work in 612) [ClassicSimilarity], result of:
          0.040811036 = score(doc=612,freq=2.0), product of:
            0.20127523 = queryWeight, product of:
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.054837555 = queryNorm
            0.20276234 = fieldWeight in 612, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.0390625 = fieldNorm(doc=612)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

While it is easy to identify whether someone has found a piece of information during a search task, it is much harder to measure how much someone has learned during the search process. Searchers who are learning often exhibit exploratory behaviors, and so current research is often focused on improving support for exploratory search. Consequently, we need effective measures of learning to demonstrate better support for exploratory search. Some approaches, such as quizzes, measure recall when learning from a fixed source of information. This research, however, focuses on techniques for measuring open-ended learning, which often involve analyzing handwritten summaries produced by participants after a task. There are two common techniques for analyzing such summaries: (a) counting facts and statements and (b) judging topic coverage. Both of these techniques, however, can be easily confounded by simple variables such as summary length. This article presents a new technique that measures depth of learning within written summaries based on Bloom's taxonomy (B.S. Bloom & M.D. Engelhart, 1956). This technique was generated using grounded theory and is designed to be less susceptible to such confounding variables. Together, these three categories of measure were compared by applying them to a large collection of written summaries produced in a task-based study, and our results provide insights into each of their strengths and weaknesses. Both fact-to-statement ratio and our own measure of depth of learning were effective while being less affected by confounding variables. Recommendations and clear areas of future work are provided to help continued research into supporting sensemaking and learning.

0.010202759 = product of:
  0.020405518 = sum of:
    0.020405518 = product of:
      0.040811036 = sum of:
        0.040811036 = weight(_text_:work in 2127) [ClassicSimilarity], result of:
          0.040811036 = score(doc=2127,freq=2.0), product of:
            0.20127523 = queryWeight, product of:
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.054837555 = queryNorm
            0.20276234 = fieldWeight in 2127, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2127)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This study demonstrates an improved conceptual foundation to support well-structured analysis of image topicality. First we present a conceptual framework for analyzing image topicality, explicating the layers, the perspectives, and the topical relevance relationships involved in modeling the topicality of art images. We adapt a generic relevance typology to image analysis by extending it with definitions and relationships specific to the visual art domain and integrating it with schemes of image-text relationships that are important for image subject indexing. We then apply the adapted typology to analyze the topical relevance relationships between 11 art images and 768 image tags assigned by art historians and librarians. The original contribution of our work is the topical structure analysis of image tags that allows the viewer to more easily grasp the content, context, and meaning of an image and quickly tune into aspects of interest; it could also guide both the indexer and the searcher to specify image tags/descriptors in a more systematic and precise manner and thus improve the match between the two parties. An additional contribution is systematically examining and integrating the variety of image-text relationships from a relevance perspective. The paper concludes with implications for relational indexing and social tagging.

0.008162207 = product of:
  0.016324414 = sum of:
    0.016324414 = product of:
      0.032648828 = sum of:
        0.032648828 = weight(_text_:work in 2671) [ClassicSimilarity], result of:
          0.032648828 = score(doc=2671,freq=2.0), product of:
            0.20127523 = queryWeight, product of:
              3.6703904 = idf(docFreq=3060, maxDocs=44218)
              0.054837555 = queryNorm
            0.16220987 = fieldWeight in 2671, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6703904 = idf(docFreq=3060, 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.