Ercan, GönençÇiçekli, İlyas2016-02-082016-02-082008-02http://hdl.handle.net/11693/26880Date of Conference: 17-23 February, 2008Conference name: International Conference on Intelligent Text Processing and Computational Linguistics CICLing 2008: Computational Linguistics and Intelligent Text ProcessingIn this paper, we attack the problem of forming extracts for text summarization. Forming extracts involves selecting the most representative and significant sentences from the text. Our method takes advantage of the lexical cohesion structure in the text in order to evaluate significance of sentences. Lexical chains have been used in summarization research to analyze the lexical cohesion structure and represent topics in a text. Our algorithm represents topics by sets of co-located lexical chains to take advantage of more lexical cohesion clues. Our algorithm segments the text with respect to each topic and finds the most important topic segments. Our summarization algorithm has achieved better results, compared to some other lexical chain based algorithms. © 2008 Springer-Verlag Berlin Heidelberg.EnglishLexical chainsLexical cohesionText summarizationAdhesionComputational linguisticsLinguisticsWord processingIntelligent text processingInternational conferencesLexical cohesion structureText processingConference Paper10.1007/978-3-540-78135-6_50