期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2017
卷号：8
期号：3
DOI：10.14569/IJACSA.2017.080317
出版社：Science and Information Society (SAI)
摘要：In paper, we have proposed a novel summarization framework to generate a quality summary by extracting Relevant-Informative-Novel (RIN) sentences from topically related document collection called as RIN-Sum. In the proposed framework, with the aim to retrieve user's relevant informative sentences conveying novel information, ranking of structured sentences has been carried out. For sentence ranking, Relevant-Informative-Novelty (RIN) ranking function is formulated in which three factors, i.e., the relevance of sentence with input query, informativeness of the sentence and the novelty of the sentence have been considered. For relevance measure instead of incorporating existing metrics, i.e., Cosine and Overlap which have certain limitations, a new relevant metric called as C-Overlap has been formulated. RIN ranking is applied on document collection to retrieve relevant sentences conveying significant and novel information about the query. These retrieved sentences are used to generate query-specific summary of multiple documents. The performance of proposed framework have been investigated using standard dataset, i.e., DUC2007 documents collection and summary evaluation tool, i.e., ROUGE.
关键词：thesai; IJACSA Volume 8 Issue 3; Text summarization; maximum marginal relevance; sentence selection; DUC2007 data collection
