Abstract
In this paper we propose a clustering-based hybrid approach for multi-document summarization which integrates sentence clustering, local recommendation and global search. For sentence clustering, we adopt a stability-based method which can determine the optimal cluster number automatically. We weight sentences with terms they contain for local sentence recommendation of each cluster. For global selection, we propose a global criterion to evaluate overall performance of a summary. Thus the sentences in the final summary are determined by not only the configuration of individual clusters but also the overall performance. This approach successfully gets top-level performance running on corpus of DUC04.
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© 2006 Springer-Verlag Berlin Heidelberg
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Nie, Y., Ji, D., Yang, L., Niu, Z., He, T. (2006). Multi-document Summarization Using a Clustering-Based Hybrid Strategy. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_53
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DOI: https://doi.org/10.1007/11880592_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45780-0
Online ISBN: 978-3-540-46237-8
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