SciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processing | Zendy

A. Ben Wagner | Zendy

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SciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processing

Author(s) -

A. Ben Wagner

Publication year - 2006

Publication title -

journal of chemical information and modeling

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.24

H-Index - 160

eISSN - 1549-960X

pISSN - 1549-9596

DOI - 10.1021/ci050481b

Subject(s) - computer science , information retrieval , set (abstract data type) , relevance (law) , plural , documentation , query expansion , web search query , query language , web query classification , search engine , natural language processing , programming language , linguistics , philosophy , political science , law

Topical search queries in SciFinder Scholar are processed through an extensive set of natural language processing algorithms that greatly enhance the relevance and comprehensiveness of the search results. Little detailed documentation on these algorithms has been published. However, a careful examination of the highlighted hit terms coupled with a comparison of results from small variations in query language reveal much additional, useful information about these algorithms. An understanding of how these algorithms work can lead to better search results and explain many unexpected results, including differing hit counts for singular versus plural query words and phrases.

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