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2006

Corpus-based and Knowledge-based Measures of Text Semantic Similarity

11 years 7 months ago
Corpus-based and Knowledge-based Measures of Text Semantic Similarity
This paper presents a method for measuring the semantic similarity of texts, using corpus-based and knowledge-based measures of similarity. Previous work on this problem has focused mainly on either large documents (e.g. text classification, information retrieval) or individual words (e.g. synonymy tests). Given that a large fraction of the information available today, on the Web and elsewhere, consists of short text snipg. abstracts of scientific documents, imagine captions, product descriptions), in this paper we focus on measuring the semantic similarity of short texts. Through experiments performed on a paraphrase data set, we show that the semantic similarity method outperforms methods based on simple lexical matching, resulting in up to 13% error rate reduction with respect to the traditional vector-based similarity metric.
Rada Mihalcea, Courtney Corley, Carlo Strapparava
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where AAAI
Authors Rada Mihalcea, Courtney Corley, Carlo Strapparava
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