Word Sense Discrimination Using Context Vector Similarity
نویسنده
چکیده
This paper presents the application of context vector similarity for the purpose of word sense discrimination during query translation. The random indexing vector space method is used to accumulate the context vectors. Pair wise similarity of the context vectors of ambiguous terms with that of anchor terms indicated the possible correct translation of a query term. Two retrieval experiments were conducted using the discriminated queries and weighted maximally expanded queries. The discriminated queries show a substantial increase in retrieval performance.
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تاریخ انتشار 2008