文章基本信息

标题：Comparison of Latent Semantic Analysis and Probabilistic Latent Semantic Analysis for Documents Clustering
其他标题：Comparison of Latent Semantic Analysis and Probabilistic Latent Semantic Analysis for Documents Clustering
作者：Kuta, Marcin ; Kitowski, Jacek
期刊名称：COMPUTING AND INFORMATICS
印刷版ISSN：1335-9150
出版年度：2014
卷号：33
期号：3
页码：652-666
语种：English
出版社：COMPUTING AND INFORMATICS
摘要：In this paper we compare usefulness of statistical techniques of dimensionality reduction for improving clustering of documents in Polish. We start with partitional and agglomerative algorithms applied to Vector Space Model. Then we investigate two transformations: Latent Semantic Analysis and Probabilistic Latent Semantic Analysis. The obtained results showed advantage of Latent Semantic Analysis technique over probabilistic model. We also analyse time and memory consumption aspects of these transformations and present runtime details for IBM BladeCenter HS21 machine.
关键词：Document clustering; latent semantic analysis; probabilistic latent semantic analysis; natural language processing;68T50; 68T05; 68T35