Abstract
Query based document summaries are important in document retrieval system to show the concise relevance of documents retrieved to a query. This paper proposes a novel method using the Non-negative Matrix Factorization (NMF) to extract the query relevant sentences from documents for query based summaries. The proposed method doesn’t need the training phase using training data comprising queries and query specific documents. And it exactly summarizes documents for the given query by using semantic features and semantic variables without complex processing like transformation of documents to graphs because the NMF have a great power to naturally extract semantic features representing the inherent structure of a document.
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Park, S., Lee, JH., Ahn, CM., Hong, J.S., Chun, SJ. (2006). Query Based Summarization Using Non-negative Matrix Factorization. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_11
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DOI: https://doi.org/10.1007/11893011_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46542-3
Online ISBN: 978-3-540-46544-7
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