Search (5 results, page 1 of 1)

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Abstract

The purpose of this study was to examine user tags that describe digitized archival collections in the field of humanities. A collection of 8,310 tags from a digital portal (Nineteenth-Century Electronic Scholarship, NINES) was analyzed to find out what attributes of primary historical resources users described with tags. Tags were categorized to identify which tags describe the content of the resource, the resource itself, and subjective aspects (e.g., usage or emotion). The study's findings revealed that over half were content-related; tags representing opinion, usage context, or self-reference, however, reflected only a small percentage. The study further found that terms related to genre or physical format of a resource were frequently used in describing primary archival resources. It was also learned that nontextual resources had lower numbers of content-related tags and higher numbers of document-related tags than textual resources and bibliographic materials; moreover, textual resources tended to have more user-context-related tags than other resources. These findings help explain users' tagging behavior and resource interpretation in primary resources in the humanities. Such information provided through tags helps information professionals decide to what extent indexing archival and cultural resources should be done for resource description and discovery, and understand users' terminology.

Date

21. 4.2016 11:23:22

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Abstract

This paper presents a methodological discussion of a study of tagging quality in subject indexing. The data analysis in the study was divided into 3 phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of the semantic values of tags. To analyze indexing consistency, this study employed the vector space model-based indexing consistency measures. An analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. To further investigate the semantic values of tags at various levels of specificity, a latent semantic analysis (LSA) was conducted. To test statistical significance for the relation between tag specificity and semantic quality, correlation analysis was conducted. This research demonstrates the potential of tags for web document indexing with a complete assessment of tagging quality and provides a basis for further study of the strengths and limitations of tagging.

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Content

This paper is derived from the author's doctoral dissertation "Usefulness of Social Tagging in Organizing and Providing Access An Analysis of Indexing Consistency and Quality." The author is deeply grateful to her dissertation committee-Dr. Linda C. Smith chairperson, Drs. Allen Renear, Miles Efron and John Unsworth. Vgl.: http://www.ergon-verlag.de/isko_ko/downloads/ko_39_2012_4_a.pdf.

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Abstract

This study investigated query modification patterns and semantic attributes in queries executed during user searches for images on the web. Its purpose was to identify whether query modification patterns were related to users' contextual factors and content sources as well as whether the patterns characterize the use of semantic attributes expressed in users' search queries in an interactive web-searching process. To this end, a collection of 970 image search queries executed by undergraduate students in a naturalistic setting was analyzed. The study's findings showed that query modification patterns were significantly associated with content sources. Among the types of query modification employed, "Reformulation" and "New" were the most frequently used. Terms related to format, object, or place associated with an image also were found to be frequently used in search queries. Terms referring to type or genre were the most frequent attributes in web image search queries, which suggests a change from previous findings of search queries in a professional context. Implications are discussed in terms of search assistants for web image searches and semantic annotation to improve image indexing.

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Date

15. 8.2004 19:22:19