Search (6 results, page 1 of 1)

0.020108584 = product of:
  0.060325753 = sum of:
    0.060325753 = product of:
      0.120651506 = sum of:
        0.120651506 = weight(_text_:indexing in 3250) [ClassicSimilarity], result of:
          0.120651506 = score(doc=3250,freq=18.0), product of:
            0.19018644 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.049684696 = queryNorm
            0.6343854 = fieldWeight in 3250, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3250)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

This paper reports on a research project that compared two different approaches for the indexing of ordinary images representing common objects: traditional indexing with controlled vocabulary and free indexing with uncontrolled vocabulary. We also compared image retrieval within two contexts: a monolingual context where the language of the query is the same as the indexing language and, secondly, a multilingual context where the language of the query is different from the indexing language. As a means of comparison in evaluating the performance of each indexing form, a simulation of the retrieval process involving 30 images was performed with 60 participants. A questionnaire was also submitted to participants in order to gather information with regard to the retrieval process and performance. The results of the retrieval simulation confirm that the retrieval is more effective and more satisfactory for the searcher when the images are indexed with the approach combining the controlled and uncontrolled vocabularies. The results also indicate that the indexing approach with controlled vocabulary is more efficient (queries needed to retrieve an image) than the uncontrolled vocabulary indexing approach. However, no significant differences in terms of temporal efficiency (time required to retrieve an image) was observed. Finally, the comparison of the two linguistic contexts reveal that the retrieval is more effective and more efficient (queries needed to retrieve an image) in the monolingual context rather than the multilingual context. Furthermore, image searchers are more satisfied when the retrieval is done in a monolingual context rather than a multilingual context.

0.017734105 = product of:
  0.053202312 = sum of:
    0.053202312 = product of:
      0.106404625 = sum of:
        0.106404625 = weight(_text_:indexing in 1089) [ClassicSimilarity], result of:
          0.106404625 = score(doc=1089,freq=14.0), product of:
            0.19018644 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.049684696 = queryNorm
            0.55947536 = fieldWeight in 1089, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1089)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

For many years, the Web became an important media for the diffusion of multilingual resources. Linguistic differenees still form a major obstacle to scientific, cultural, and educational exchange. Besides this linguistic diversity, a multitude of databases and collections now contain documents in various formats, which may also adversely affect the retrieval process. This paper describes a research project aiming to verify the existing relations between two indexing approaches: traditional image indexing recommending the use of controlled vocabularies or free image indexing using uncontrolled vocabulary, and their respective performance for image retrieval, in a multilingual context. This research also compares image retrieval within two contexts: a monolingual context where the language of the query is the same as the indexing language; and a multilingual context where the language of the query is different from the indexing language. This research will indicate whether one of these indexing approaches surpasses the other, in terms of effectiveness, efficiency, and satisfaction of the image searchers. This paper presents the context and the problem statement of the research project. The experiment carried out is also described, as well as the data collection methods

0.016418591 = product of:
  0.049255773 = sum of:
    0.049255773 = product of:
      0.09851155 = sum of:
        0.09851155 = weight(_text_:indexing in 4100) [ClassicSimilarity], result of:
          0.09851155 = score(doc=4100,freq=12.0), product of:
            0.19018644 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.049684696 = queryNorm
            0.51797354 = fieldWeight in 4100, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4100)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems. Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.

0.009384007 = product of:
  0.02815202 = sum of:
    0.02815202 = product of:
      0.05630404 = sum of:
        0.05630404 = weight(_text_:indexing in 4995) [ClassicSimilarity], result of:
          0.05630404 = score(doc=4995,freq=2.0), product of:
            0.19018644 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.049684696 = queryNorm
            0.29604656 = fieldWeight in 4995, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4995)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

This paper discusses the goals and results of the research project Perseus-a as an attempt to improve information retrieval of digital images by automatically connecting them with text-based descriptions. The development uses the image collection of prometheus, the distributed digital image archive for research and studies, the articles of the digitized Reallexikon zur Deutschen Kunstgeschichte, art historical terminological resources and classification data, and an open source system for linguistic and statistic automatic indexing called lingo.

0.0067028617 = product of:
  0.020108584 = sum of:
    0.020108584 = product of:
      0.04021717 = sum of:
        0.04021717 = weight(_text_:indexing in 4117) [ClassicSimilarity], result of:
          0.04021717 = score(doc=4117,freq=2.0), product of:
            0.19018644 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.049684696 = queryNorm
            0.21146181 = fieldWeight in 4117, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4117)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

To enable and guide effective metadata creation it is essential to understand the structure and patterns of the activities of the community around the photographs, resources used, and scale and quality of the socially created metadata relative to the metadata and knowledge already encoded in existing knowledge organization systems. This article presents an analysis of Flickr member discussions around the photographs of the Library of Congress photostream in Flickr. The article also reports on an analysis of the intrinsic and relational quality of the photostream tags relative to two knowledge organization systems: the Thesaurus for Graphic Materials (TGM) and the Library of Congress Subject Headings (LCSH). Thirty seven percent of the original tag set and 15.3% of the preprocessed set (after the removal of tags with fewer than three characters and URLs) were invalid or misspelled terms. Nouns, named entity terms, and complex terms constituted approximately 77% of the preprocessed set. More than a half of the photostream tags were not found in the TGM and LCSH, and more than a quarter of those terms were regular nouns and noun phrases. This suggests that these terms could be complimentary to more traditional methods of indexing using controlled vocabularies.

0.0033657951 = product of:
  0.010097385 = sum of:
    0.010097385 = product of:
      0.02019477 = sum of:
        0.02019477 = weight(_text_:22 in 4054) [ClassicSimilarity], result of:
          0.02019477 = score(doc=4054,freq=2.0), product of:
            0.17398734 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049684696 = queryNorm
            0.116070345 = fieldWeight in 4054, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0234375 = fieldNorm(doc=4054)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

6. 1.2011 11:22:12