Abstract
This chapter presents an overview of methods for measuring the similarity of words and texts, using corpus-based and knowledge-based measures of semantic similarity. It describes several word-to-word measures of similarity, using knowledge resources such as WordNet, or large corpora of raw or encyclopedic texts, and shows how these word-based measures can be combined into a text-to-text similarity metric that can be effectively applied to similarity or paraphrase recognition. The metrics are evaluated and compared using a number of experiments performed on several word and text similarity datasets. The chapter concludes by discussing the main techniques proposed to date, and discussing the emerging trends.
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