Text summarization using Latent Semantic Analysis

Authors:
Makbule Gulcin Ozsoy;Ferda Nur Alpaslan;Ilyas Cicekli
Affiliations:
Department of Computer Engineering, Middle East TechnicalUniversity, Turkey;Department of Computer Engineering, Middle East TechnicalUniversity, Turkey;Department of Computer Engineering, Hacettepe University,Turkey
Venue:
Journal of Information Science
Year:
2011

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Abstract

Text summarization solves the problem of presenting the information needed by a user in a compact form. There are different approaches to creating well-formed summaries. One of the newest methods is the Latent Semantic Analysis (LSA). In this paper, different LSA-based summarization algorithms are explained, two of which are proposed by the authors of this paper. The algorithms are evaluated on Turkish and English documents, and their performances are compared using their ROUGE scores. One of our algorithms produces the best scores and both algorithms perform equally well on Turkish and English document sets.