Engineering Commons^™

Investigation On How To Improve Latent Semantic Analysis Performance, Thao Doan

Inquiry: The University of Arkansas Undergraduate Research Journal

Latent Semantic Analysis (LSA) is a matching technique capable of recognizing the semantic relationships of data that ordinary techniques such as string matching cannot. This is especially valuable for data integration applications, like those of Acxiom, where data items are usually related by context, rather than in a literal match. Even though it has been shown that LSA is 30% more effective in finding and ranking relevant pieces of information than existing string-by-string matching techniques (Deerwester et al., 1990; Dumais, 1995), the performance of the LSA seems to be affected by the presence of shared words, or “noise”, in data. …