Richardson, R.; Smeaton, A.F.: Automatic word sense disambiguation in a KBIR application (1995)
0.01
0.0063299187 = product of:
0.03481455 = sum of:
0.008771234 = weight(_text_:information in 5796) [ClassicSimilarity], result of:
0.008771234 = score(doc=5796,freq=2.0), product of:
0.05652887 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.032201413 = queryNorm
0.1551638 = fieldWeight in 5796, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0625 = fieldNorm(doc=5796)
0.026043316 = weight(_text_:retrieval in 5796) [ClassicSimilarity], result of:
0.026043316 = score(doc=5796,freq=2.0), product of:
0.09740654 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.032201413 = queryNorm
0.26736724 = fieldWeight in 5796, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=5796)
0.18181819 = coord(2/11)
- Abstract
- Discusses the implementation and design of an automatic word sense disambiguator. The semantic tagger is used in an overall Knowledge Based Information Retrieval (KBIR) system which uses a WordNet derived knowledge base (KB) and 2 independent semantic similarity estimators. The KB is used as a controlled vocabulary to represent documents and queries and the semantic similarity estimators are employed to determine the degree of relatedness between the KB representations
