Search (10 results, page 1 of 1)

0.03341625 = product of:
  0.0668325 = sum of:
    0.040692065 = weight(_text_:social in 2127) [ClassicSimilarity], result of:
      0.040692065 = score(doc=2127,freq=2.0), product of:
        0.1847249 = queryWeight, product of:
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.046325076 = queryNorm
        0.22028469 = fieldWeight in 2127, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2127)
    0.026140431 = product of:
      0.052280862 = sum of:
        0.052280862 = weight(_text_:aspects in 2127) [ClassicSimilarity], result of:
          0.052280862 = score(doc=2127,freq=2.0), product of:
            0.20938325 = queryWeight, product of:
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.046325076 = queryNorm
            0.2496898 = fieldWeight in 2127, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2127)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

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.

0.024918701 = product of:
  0.099674806 = sum of:
    0.099674806 = weight(_text_:social in 4972) [ClassicSimilarity], result of:
      0.099674806 = score(doc=4972,freq=12.0), product of:
        0.1847249 = queryWeight, product of:
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.046325076 = queryNorm
        0.5395851 = fieldWeight in 4972, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4972)
  0.25 = coord(1/4)

Abstract

Sentiment analysis is concerned with the automatic extraction of sentiment-related information from text. Although most sentiment analysis addresses commercial tasks, such as extracting opinions from product reviews, there is increasing interest in the affective dimension of the social web, and Twitter in particular. Most sentiment analysis algorithms are not ideally suited to this task because they exploit indirect indicators of sentiment that can reflect genre or topic instead. Hence, such algorithms used to process social web texts can identify spurious sentiment patterns caused by topics rather than affective phenomena. This article assesses an improved version of the algorithm SentiStrength for sentiment strength detection across the social web that primarily uses direct indications of sentiment. The results from six diverse social web data sets (MySpace, Twitter, YouTube, Digg, Runners World, BBC Forums) indicate that SentiStrength 2 is successful in the sense of performing better than a baseline approach for all data sets in both supervised and unsupervised cases. SentiStrength is not always better than machine-learning approaches that exploit indirect indicators of sentiment, however, and is particularly weaker for positive sentiment in news-related discussions. Overall, the results suggest that, even unsupervised, SentiStrength is robust enough to be applied to a wide variety of different social web contexts.

0.022747558 = product of:
  0.09099023 = sum of:
    0.09099023 = weight(_text_:social in 2669) [ClassicSimilarity], result of:
      0.09099023 = score(doc=2669,freq=10.0), product of:
        0.1847249 = queryWeight, product of:
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.046325076 = queryNorm
        0.49257156 = fieldWeight in 2669, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2669)
  0.25 = coord(1/4)

Abstract

In this paper, we focus on applying sentiment analysis to resources from online art collections, by exploiting, as information source, tags intended as textual traces that visitors leave to comment artworks on social platforms. We present a framework where methods and tools from a set of disciplines, ranging from Semantic and Social Web to Natural Language Processing, provide us the building blocks for creating a semantic social space to organize artworks according to an ontology of emotions. The ontology is inspired by the Plutchik's circumplex model, a well-founded psychological model of human emotions. Users can be involved in the creation of the emotional space, through a graphical interactive interface. The development of such semantic space enables new ways of accessing and exploring art collections. The affective categorization model and the emotion detection output are encoded into W3C ontology languages. This gives us the twofold advantage to enable tractable reasoning on detected emotions and related artworks, and to foster the interoperability and integration of tools developed in the Semantic Web and Linked Data community. The proposal has been evaluated against a real-word case study, a dataset of tagged multimedia artworks from the ArsMeteo Italian online collection, and validated through a user study.

Footnote

Beitrag in einem Themenheft "Emotion and sentiment in social and expressive media"

0.010456172 = product of:
  0.041824687 = sum of:
    0.041824687 = product of:
      0.083649375 = sum of:
        0.083649375 = weight(_text_:aspects in 4707) [ClassicSimilarity], result of:
          0.083649375 = score(doc=4707,freq=2.0), product of:
            0.20938325 = queryWeight, product of:
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.046325076 = queryNorm
            0.39950368 = fieldWeight in 4707, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.0625 = fieldNorm(doc=4707)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

0.010173016 = product of:
  0.040692065 = sum of:
    0.040692065 = weight(_text_:social in 2667) [ClassicSimilarity], result of:
      0.040692065 = score(doc=2667,freq=2.0), product of:
        0.1847249 = queryWeight, product of:
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.046325076 = queryNorm
        0.22028469 = fieldWeight in 2667, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2667)
  0.25 = coord(1/4)

Footnote

Beitrag in einem Themenheft "Emotion and sentiment in social and expressive media"

0.009149151 = product of:
  0.036596604 = sum of:
    0.036596604 = product of:
      0.07319321 = sum of:
        0.07319321 = weight(_text_:aspects in 5170) [ClassicSimilarity], result of:
          0.07319321 = score(doc=5170,freq=2.0), product of:
            0.20938325 = queryWeight, product of:
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.046325076 = queryNorm
            0.3495657 = fieldWeight in 5170, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5170)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

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.

0.008138414 = product of:
  0.032553654 = sum of:
    0.032553654 = weight(_text_:social in 2671) [ClassicSimilarity], result of:
      0.032553654 = score(doc=2671,freq=2.0), product of:
        0.1847249 = queryWeight, product of:
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.046325076 = queryNorm
        0.17622775 = fieldWeight in 2671, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9875789 = idf(docFreq=2228, maxDocs=44218)
          0.03125 = fieldNorm(doc=2671)
  0.25 = coord(1/4)

Footnote

Beitrag in einem Themenheft "Emotion and sentiment in social and expressive media"

0.007842129 = product of:
  0.031368516 = sum of:
    0.031368516 = product of:
      0.06273703 = sum of:
        0.06273703 = weight(_text_:aspects in 3953) [ClassicSimilarity], result of:
          0.06273703 = score(doc=3953,freq=2.0), product of:
            0.20938325 = queryWeight, product of:
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.046325076 = queryNorm
            0.29962775 = fieldWeight in 3953, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.5198684 = idf(docFreq=1308, maxDocs=44218)
              0.046875 = fieldNorm(doc=3953)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

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.

0.0055476134 = product of:
  0.022190453 = sum of:
    0.022190453 = product of:
      0.044380907 = sum of:
        0.044380907 = weight(_text_:22 in 4888) [ClassicSimilarity], result of:
          0.044380907 = score(doc=4888,freq=4.0), product of:
            0.16222252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046325076 = 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)
  0.25 = coord(1/4)

Date

22. 1.2012 13:02:10

Source

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

0.004707306 = product of:
  0.018829225 = sum of:
    0.018829225 = product of:
      0.03765845 = sum of:
        0.03765845 = weight(_text_:22 in 1416) [ClassicSimilarity], result of:
          0.03765845 = score(doc=1416,freq=2.0), product of:
            0.16222252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046325076 = 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)
  0.25 = coord(1/4)

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