Latent Semantic Analysis
نویسنده
چکیده
Latent Semantic Analysis (LSA) is a technique for comparing texts using a vector-based representation that is learned from a corpus. This article begins with a description of the history of LSA and its basic functionality. LSA enjoys both theoretical support and empirical results that show how it matches human behavior. A number of the experiments that compare LSA with humans are described here. The article also describes a few of the many successful applications of LSA to text-processing problems, and finishes by presenting a number of current research directions.
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تاریخ انتشار 1999