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Computing semantic relatedness using Wikipedia-based explicit semantic analysis-英文文献
Computing Semantic Relatedness using
Wikipedia-based Explicit Semantic Analysis
Evgeniy Gabrilovich and Shaul Markovitch
Department of Computer Science
Technion—Israel Institute of Technology, 32000 Haifa, Israel
{gabr,shaulm}@cs.technion.ac.il
Abstract We propose a novel method, called Explicit Semantic
Analysis (ESA), for fine-grained semantic representation of
Computing semantic relatedness of natural lan-
unrestricted natural language texts. Our method represents
guage texts requires access to vast amounts of meaning in a high-dimensional space of natural concepts de-
common-sense and domain-specific world knowl- rived from Wikipedia (), the
edge. We propose Explicit Semantic Analysis
largest encyclopedia in existence. We employ text classi-
(ESA), a novel method that represents the mean- fication techniques that allow us to explicitly represent the
ing of texts in a high-dimensional space of concepts meaning of any text in terms of Wikipedia-based concepts.
derived from Wikipedia. We use machine learning
We evaluate the effectiveness of our method on automatically
techniques to explicitly represent the meaning of computing the degree of semantic relatedness be
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