Text summarization using Latent Semantic Analysis

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Date

2011-08-01

Author

Ozsoy, Makbule Gulcin
Alpaslan, Ferda Nur
Çiçekli, İlyas

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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.

Subject Keywords

Library and Information Sciences, Information Systems

URI

https://hdl.handle.net/11511/39341

Journal

JOURNAL OF INFORMATION SCIENCE

DOI

https://doi.org/10.1177/0165551511408848

Collections

Department of Computer Engineering, Article

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Citation Formats

M. G. Ozsoy, F. N. Alpaslan, and İ. Çiçekli, “Text summarization using Latent Semantic Analysis,” JOURNAL OF INFORMATION SCIENCE, pp. 405–417, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39341.