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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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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.