Otomatik özet ve anahtar kelime çıkarma

ABSTRACTAUTOMATED TEXT SUMMARIZATION ANDKEYPHRASE EXTRACTIONGünenş Ercano cM.S. in Computer Engineering˙Supervisor: Asst. Prof. Dr. Ilyas CişeklişcSeptember, 2006As the number of electronic documents increase rapidly, the need for faster tech-niques to asses the relevance of documents emerges. A summary can be consideredas a concise representation of the underlying text. To form an ideal summary, afull understanding of the document is essential. For computers, full understand-ing is difficult, if not impossible. Thus, selecting important sentences from theoriginal text and presenting these sentences as a summary is a common techniquein automated text summarization research.The lexical cohesion structure of the text can be exploited to determine theimportance of a sentence/phrase. Lexical chains are useful tools to analyze thelexical cohesion structure in a text. This thesis discusses our research on auto-mated text summarization and keyphrase extraction using lexical chains. We in-vestigate the effect of the use of lexical cohesion features in keyphrase extraction,with a supervised machine learning algorithm. Our summarization algorithmconstructs the lexical chains, detects topics roughly from lexical chains, segmentsthe text with respect to the topics and selects the most important sentences. Ourexperiments show that lexical cohesion based features improve keyphrase extrac-tion. Our summarization algorithm has achieved good results, compared to someother lexical cohesion based algorithms.Keywords: Automated Text Summarization, Keyphrase Extraction, LexicalChain, Lexical Cohesion, Natural Language Processing.iii