Hc. Chen et al., ALLEVIATING SEARCH UNCERTAINTY THROUGH CONCEPT ASSOCIATIONS - AUTOMATIC-INDEXING, COOCCURRENCE ANALYSIS, AND PARALLEL COMPUTING, Journal of the American Society for Information Science, 49(3), 1998, pp. 206-216
Citations number
38
Categorie Soggetti
Information Science & Library Science","Computer Science Information Systems","Computer Science Information Systems
In this article, we report research on an algorithmic approach to alle
viating search uncertainty in a large information space. Grounded on o
bject filtering, automatic indexing, and co-occurrence analysis, we pe
rformed a large-scale experiment using a parallel supercomputer (SGI P
ower Challenge) to analyze 400,000+ abstracts in an INSPEC computer en
gineering collection. Two system-generated thesauri, one based on a co
mbined object filtering and automatic indexing method, and the other b
ased on automatic indexing only, were compared with the human-generate
d INSPEC subject thesaurus. Our user evaluation revealed that the syst
em-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 and thereby reduce search uncertainty.