Chen, H.; Martinez, J.; Kirchhoff, A.; Ng, T.D.; Schatz, B.R.: Alleviating search uncertainty through concept associations : automatic indexing, co-occurence analysis, and parallel computing (1998)
0.03
0.03148115 = product of:
0.0629623 = sum of:
0.0629623 = product of:
0.1259246 = sum of:
0.1259246 = weight(_text_:thesaurus in 5202) [ClassicSimilarity], result of:
0.1259246 = score(doc=5202,freq=6.0), product of:
0.23732872 = queryWeight, product of:
4.6210785 = idf(docFreq=1182, maxDocs=44218)
0.051357865 = queryNorm
0.5305915 = fieldWeight in 5202, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
4.6210785 = idf(docFreq=1182, maxDocs=44218)
0.046875 = fieldNorm(doc=5202)
0.5 = coord(1/2)
0.5 = coord(1/2)
- 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