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  • × author_ss:"Kim, Y."
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  1. Buckland, M.; Chen, A.; Chen, H.M.; Kim, Y.; Lam, B.; Larson, R.; Norgard, B.; Purat, J.; Gey, F.: Mapping entry vocabulary to unfamiliar metadata vocabularies (1999) 0.00 
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    Footnote
    Vgl.: http://www.dlib.org/dlib/january99/buckland/01buckland.html und http://www.sims.berkeley.edu/research/metadata/oasis.html.
  2. Kim, Y.; Norgard, B.; Chen, A.; Gey, F.: Using ordinary language in access metadata of divers types of information resources : trade classifications and numeric data (1999) 0.00 
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    Abstract
    In this paper, we deal with the retrieval of numeric data from information sources that present special challenges. We describe a new method to deal with the challenge of accessing this special type of data indexed by unfamiliar metadata vocabularies. The purpose of our Entry Vocabulary Module (EVM) approach is to facilitate use of unfamiliar metadata vocabularies to access data. We have developed a method of mapping language found in text of titles and abstracts to metadata vocabulary terms. This enables people to use ordinary language queries to search databases indexed with unfamiliar metadata vocabularies. Numeric data lacks textual resources we draw upon to build associations between ordinary language and metadata terms. Therefore, we have extended the EVM approach to deal with numeric database searching
    Imprint
    Medford, NJ : Information Today
    Series
    Proceedings of the American Society for Information Science; vol.36
    Source
    Knowledge: creation, organization and use. Proceedings of the 62nd Annual Meeting of the American Society for Information Science, 31.10.-4.11.1999. Ed.: L. Woods
  3. Clark, M.; Kim, Y.; Kruschwitz, U.; Song, D.; Albakour, D.; Dignum, S.; Beresi, U.C.; Fasli, M.; Roeck, A De: Automatically structuring domain knowledge from text : an overview of current research (2012) 0.00 
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    Abstract
    This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing, information retrieval and semantic web technology. Inspired by the ubiquitous propagation of domain model structures that are emerging in several research disciplines, we give an overview of the current research landscape and some techniques and approaches. We will also discuss trade-offs between different approaches and point to some recent trends.
    Source
    Information processing and management. 48(2012) no.3, S.552-568
  4. Kim, Y.; Stanton, J.M.: Institutional and individual factors affecting scientists' data-sharing behaviors : a multilevel analysis (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.4, S.776-799
  5. Kim, Y.; Seo, J.; Croft, W.B.; Smith, D.A.: Automatic suggestion of phrasal-concept queries for literature search (2014) 0.00 
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    Source
    Information processing and management. 50(2014) no.4, S.568-583
  6. Kim, Y.; Yoon, A.: Scientists' data reuse behaviors : a multilevel analysis (2017) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.12, S.2709-2719

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