Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Text summarization using Latent Semantic Analysis
Download
index.pdf
Date
2011-08-01
Author
Ozsoy, Makbule Gulcin
Alpaslan, Ferda Nur
Çiçekli, İlyas
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
3
views
11
downloads
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