Document (#23201)

Author
Chen, H.
Martinez, J.
Kirchhoff, A.
Ng, T.D.
Schatz, B.R.
Title
Alleviating search uncertainty through concept associations : automatic indexing, co-occurence analysis, and parallel computing
Source
Journal of the American Society for Information Science. 49(1998) no.3, S.206-216
Year
1998
Abstract
In this article, we report research on an algorithmic approach to alleviating search uncertainty in a large information space. Grounded on object filtering, automatic indexing, and co-occurence analysis, we performed a large-scale experiment using a parallel supercomputer (SGI Power Challenge) to analyze 400.000+ abstracts in an INSPEC computer engineering collection. Two system-generated thesauri, one based on a combined object filtering and automatic indexing method, and the other based on automatic indexing only, were compaed with the human-generated INSPEC subject thesaurus. Our user evaluation revealed that the system-generated thesauri were better than the INSPEC thesaurus in 'concept recall', but in 'concept precision' the 3 thesauri were comparable. Our analysis also revealed that the terms suggested by the 3 thesauri were complementary and could be used to significantly increase 'variety' in search terms the thereby reduce search uncertainty
Theme
Konzeption und Anwendung des Prinzips Thesaurus
Retrievalstudien
Semantisches Umfeld in Indexierung u. Retrieval

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