Search (4 results, page 1 of 1)

  • × author_ss:"Wu, S."
  • × year_i:[2010 TO 2020}
  1. Wu, S.; Fan, Y.: Music literature indexing : comparing users' free-text queries and controlled vocabularies (2018) 0.02
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    Abstract
    This study examined the characteristics of users' free-text queries submitted to RILM Abstracts of Music Literature (a music literature database), and compared those queries with the controlled vocabularies used by RILM. Search-log analysis identified 11 categories of user-created search terms, and mapped each user-created search term to RILM's index terms, assessing whether it was a perfect match, a partial match, or no match. Only 30.04% of the user-created search terms did not match RILM's index terms. Most of the partial-matching and non-matching user-created search terms were personal names, work titles, and topical terms. Suggestions are offered to enhance RILM's controlled vocabularies.
  2. Wu, S.; Fan, Y.: Music literature indexing : comparing users' free-text queries and controlled vocabularies (2018) 0.02
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    Abstract
    This study examined the characteristics of users' free-text queries submitted to RILM Abstracts of Music Literature (a music literature database), and compared those queries with the controlled vocabularies used by RILM. Search-log analysis identified 11 categories of user-created search terms, and mapped each user-created search term to RILM's index terms, assessing whether it was a perfect match, a partial match, or no match. Only 30.04% of the user-created search terms did not match RILM's index terms. Most of the partial-matching and non-matching user-created search terms were personal names, work titles, and topical terms. Suggestions are offered to enhance RILM's controlled vocabularies.
  3. Jörgensen, C.; Stvilia, B.; Wu, S.: Assessing the relationships among tag syntax, semantics, and perceived usefulness (2014) 0.01
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    Abstract
    With the recent interest in socially created metadata as a potentially complementary resource for image description in relation to established tools such as thesauri and other forms of controlled vocabulary, questions remain about the quality and reuse value of these metadata. This study describes and examines a set of tags using quantitative and qualitative methods and assesses relationships among categories of image tags, tag assignment order, and users' perceptions of usefulness of index terms and user-contributed tags. The study found that tags provide much descriptive information about an image but that users also value and trust controlled vocabulary terms. The study found no correlation between tag length and assignment order, and tag length and its perceived usefulness. The findings of this study can contribute to the design of controlled vocabularies, indexing processes, and retrieval systems for images. In particular, the findings of the study can advance the understanding of image tagging practices, tag facet/category distributions, relative usefulness and importance of these categories to the user, and potential mechanisms for identifying useful terms.
  4. Zhao, R.; Wu, S.: ¬The network pattern of journal knowledge transfer in library and information science in China (2014) 0.01
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    Abstract
    Using the library and information science journals 2003-2012 in Nanjing University's Chinese Social Sciences Citation Index as data sources, the paper reveals the citation structure implied in these journals by applying social network analysis. Results show that, first, journal knowledge transfer activity in library and information science is frequent, and both the level of knowledge and discipline integration as well as the knowledge gap influenced knowledge transfer activity. According to the out-degree and in-degree, journals can be divided into three kinds. Second, based on professional bias and citation frequency, the knowledge transfer network can be divided into four blocks. With the change of discipline capacity and knowledge gap among journals, the "core-periphery" structure of the knowledge transfer network is getting weaker. Finally, regions of the knowledge transfer network evolved from a "weak-weak" subgroup to a "strong-weak" subgroup or a "weak-strong" subgroup, and then move to a "strong-strong" subgroup.