-
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)
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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.
- Source
- D-Lib magazine. 5(1999) no.1, xx S
-
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)
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- Date
- 29. 1.2016 18:29:51
-
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)
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- Date
- 29. 9.2001 21:07:00
-
Buckland, M.K.; Chen, A.; Gebbie, M.; Kim, Y.; Norgard, B.: Variation by subdomain in indexes to knowledge organization systems (2000)
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- Source
- Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al
-
Gudykunst, W.; Kim, Y.: Communicating with strangers : an approach to intercultural communication (1992)
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- Date
- 1. 3.2008 14:23:16
-
Kim, Y.; Seo, J.; Croft, W.B.; Smith, D.A.: Automatic suggestion of phrasal-concept queries for literature search (2014)
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- Abstract
- Both general and domain-specific search engines have adopted query suggestion techniques to help users formulate effective queries. In the specific domain of literature search (e.g., finding academic papers), the initial queries are usually based on a draft paper or abstract, rather than short lists of keywords. In this paper, we investigate phrasal-concept query suggestions for literature search. These suggestions explicitly specify important phrasal concepts related to an initial detailed query. The merits of phrasal-concept query suggestions for this domain are their readability and retrieval effectiveness: (1) phrasal concepts are natural for academic authors because of their frequent use of terminology and subject-specific phrases and (2) academic papers describe their key ideas via these subject-specific phrases, and thus phrasal concepts can be used effectively to find those papers. We propose a novel phrasal-concept query suggestion technique that generates queries by identifying key phrasal-concepts from pseudo-labeled documents and combines them with related phrases. Our proposed technique is evaluated in terms of both user preference and retrieval effectiveness. We conduct user experiments to verify a preference for our approach, in comparison to baseline query suggestion methods, and demonstrate the effectiveness of the technique with retrieval experiments.
