Text summarization model based on maximum coverage problem and its variant

Authors:
Hiroya Takamura;Manabu Okumura
Affiliations:
Tokyo Institute of Technology, Yokohama;Tokyo Institute of Technology, Yokohama
Venue:
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Year:
2009

Citing 11
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Abstract

We discuss text summarization in terms of maximum coverage problem and its variant. We explore some decoding algorithms including the ones never used in this summarization formulation, such as a greedy algorithm with performance guarantee, a randomized algorithm, and a branch-and-bound method. On the basis of the results of comparative experiments, we also augment the summarization model so that it takes into account the relevance to the document cluster. Through experiments, we showed that the augmented model is superior to the best-performing method of DUC'04 on ROUGE-1 without stopwords.