Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy

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Summary

This paper presents a new approach for measuring semantic similarity/distance between words and concepts that combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantified with the computational evidence derived from a distributional analysis of corpus data.

Type
preprint
Published
1997-08-01
Cited by
3,496
References
19
Access
Open access

Keywords

Semantic similarity, Computer science, Artificial intelligence, Taxonomy (biology), Natural language processing

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