ESUM: An Efficient System for Query-Specific Multi-document Summarization
In this paper, we address the problem of generating a query-specific extractive summary in a an efficient manner for a given set of documents. In many of the current solutions, the entire collection of documents is modeled as a single graph which is used for summary generation. Unlike these approaches, in this paper, we model each individual document as a graph and generate a query-specific summary for it. These individual summaries are then intelligently combined to produce the final summary. This approach greatly reduces the computational complexity.
KeywordsEfficient summarization Coherent and Non-redundant summaries
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- 2.Erkan, G., Radev, D.R.: LexPageRank: Prestige in multi-document text summarization. In: Proceedings of EMNLP, Barcelona, Spain, July 2004, pp. 365–371. ACL (2004)Google Scholar
- 3.Mihalcea, R.: Graph-based ranking algorithms for sentence extraction, applied to text summarization. In: Proceedings of the ACL 2004 on Interactive poster and demonstration sessions, Barcelona, Spain, p. 20. ACL (2004)Google Scholar
- 4.Otterbacher, J., Erkan, G., Radev, D.R.: Using random walks for question-focused sentence retrieval. In: HLT 2005: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Vancouver, British Columbia, Canada, ACL, pp. 915–922. ACL (2005)Google Scholar
- 5.Carbonell, J.G., Goldstein, J.: The use of mmr, diversity-based reranking for reordering documents and producing summaries. In: SIGIR, Melbourne, Australia, pp. 335–336. ACM, New York (1998)Google Scholar
- 6.Wang, D., Li, T., Zhu, S., Ding, C.: Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization. In: SIGIR 2008: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, Singapore, pp. 307–314. ACM, New York (2008)Google Scholar
- 7.Radev, D.R., Jing, H., Budzikowska, M.: Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies. In: NAACL-ANLP 2000 Workshop on Automatic summarization, Seattle, Washington, pp. 21–30. ACL (2000)Google Scholar