Paper: Text Summarization of Turkish Texts using Latent Semantic Analysis

ACL ID C10-1098
Title Text Summarization of Turkish Texts using Latent Semantic Analysis
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

Text summarization solves the problem of extracting important information from huge amount of text data. There are vari- ous 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 summariza- tion algorithms are explained and two new LSA based summarization algo- rithms are proposed. The algorithms are evaluated on Turkish documents, and their performances are compared using their ROUGE-L scores. One of our algo- rithms produces the best scores.