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Sentence Extraction by Spreading Activation through Sentence Similarity
Naoaki OKAZAKI Yutaka MATSUO Naohiro MATSUMURA Mitsuru ISHIZUKA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2003/09/01
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Text Processing for Information Access)
summarization, extraction, sentence similarity, spreading activation,
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Although there has been a great deal of research on automatic summarization, most methods rely on statistical methods, disregarding relationships between extracted textual segments. We propose a novel method to extract a set of comprehensible sentences which centers on several key points to ensure sentence connectivity. It features a similarity network from documents with a lexical dictionary, and spreading activation to rank sentences. We show evaluation results of a multi-document summarization system based on the method participating in a competition of summarization, TSC (Text Summarization Challenge) task, organized by the third NTCIR project.