Text Summarization of Turkish Texts using Latent Semantic Analysis

摘要：

Text summarization solves the problem of extracting important information from huge amount of text data. There are various methods in the literature that aim to find out well-formed summaries. One of the most commonly used methods is the Latent Semantic Analysis (LSA). In this paper, different LSA based summarization algorithms are explained and two new LSA based summarization algorithms are proposed. The algorithms are evaluated on Turkish documents, and their performances are compared using their ROUGE-L scores. One of our algorithms produces the best scores.

作者: Makbule Gulcin Ozsoy Ilyas Cicekli Ferda Nur Alpaslan

作者单位: Dept. of Computer Eng.Middle East Tech. Univ. Dept. of Computer Eng.Bilkent University

会议类型: 国际会议

会议名称: The 23rd International Conference on Computational Linguistics(第23届国际计算语言学大会)

会议地点: 北京

会议语种:英文

页码: 869-876

在线出版日期: 2010-08-01（万方平台首次上网日期，不代表论文的发表时间）