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Although social data has been investigated and discussed regarding its impact on indexing and retrieval performance on the web, there has been little research conducted on storing or linking social data and identifying bibliographic relationships among social data for further use of social data. In this paper, we discuss our work in progress that aims to develop a social metadata repository which would be an important implication for making social data more valuable and reusable for searching and retrieval. We describe FRBR (Functional Requirements of Bibliographic Records) conceptual model's Entity-Relationship (ER) view on bibliographic relationships and demonstrate how social metadata are encoded in RDA (Resource Description and Access) and how the implicit bibliographic relationships of social data are explicitly represented as RDF (Resource Description Framework) triples (Subject - Predicates - Objects) with links to external sources. We believe that the shareable and linked metadata repository of social data is remarkably significant, not only because it supports the accessibility to related documents, but also because it is clarifying the implicit semantic relationships among social data.
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Due to the large volume and complexity of data, exploring data using visual analytics has become more helpful to interpret and analyze it. The box plot is one of graphical ways and is the most common technique for presenting and summarizing statistics. In this paper, we focus on discussing the tagging patterns by integrating visualization assessment using the box plot with the Shapiro-Wilk test. © 2015 Author.
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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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This poster presents preliminary findings of user tag analysis in the domain of consumer health information. To obtain user terms, 36,205 tags from 38 consumer health information sites were collected from delicious.com. Content analysis was applied to identify the dimensions and types of the collected tags. The preliminary findings showed that user generated tags covers a variety of aspects of health information, ranging from general terms, subject terms, knowledge type, and to audience. General terms and subject terms were observed dominantly by showing 31.7% and 22.8% respectively. © 2015 Authors.
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