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Computing Semantic Relatedness Using Wikipedia …

Computing Semantic Relatedness usingWikipedia- based Explicit Semantic AnalysisEvgeniy GabrilovichandShaul MarkovitchDepartment of Computer ScienceTechnion Israel Institute of Technology, 32000 Haifa, Semantic Relatedness of natural lan-guage texts requires access to vast amounts ofcommon-sense and domain-specific world knowl-edge. We propose Explicit Semantic Analysis(ESA), a novel method that represents the mean-ing of texts in a high-dimensional space of conceptsderived from Wikipedia . We use machine learningtechniques to explicitly represent the meaning ofany text as a weighted vector of Wikipedia -basedconcepts. Assessing the Relatedness of texts inthis space amounts to comparing the correspondingvectors Using conventional metrics ( , cosine).Compared with the previous state of the art, usingESA results in substantial improvements in corre-lation of computed Relatedness scores with humanjudgments: fromr= individualwords and fromr= texts.

Computing Semantic Relatedness using Wikipedia-based Explicit Semantic Analysis Evgeniy Gabrilovich and Shaul Markovitch Department of Computer Science

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