Modern Information Retrieval
Cross-document summarization by concept classification
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Document clustering with committees
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Summarization beyond sentence extraction: a probabilistic approach to sentence compression
Artificial Intelligence
Multidocument summarization: An added value to clustering in interactive retrieval
ACM Transactions on Information Systems (TOIS)
A Study of Chinese Text Summarization Using Adaptive Clustering of Paragraphs
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Information fusion in the context of multi-document summarization
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Effect of Preprocessing on Extractive Summarization with Maximal Frequent Sequences
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Text Summarization by Sentence Extraction Using Unsupervised Learning
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Using negative voting to diversify answers in non-factoid question answering
Proceedings of the 18th ACM conference on Information and knowledge management
Terms derived from frequent sequences for extractive text summarization
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Web news summarization via soft clustering algorithm
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
An improved web information summarization based on SSSC
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 3
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In this paper, we propose a novel multi-document summarization strategy based on Basic Element (BE) vector clustering. In this strategy, sentences are represented by BE vectors instead of word or term vectors before clustering. BE is a head-modifier-relation triple representation of sentence content, and it is more precise to use BE as semantic unit than to use word. The BE-vector clustering is realized by adopting the k-means clustering method, and a novel clustering analysis method is employed to automatically detect the number of clusters, K. The experimental results indicate a superiority of the proposed strategy over the traditional summarization strategy based on word vector clustering. The summaries generated by the proposed strategy achieve a ROUGE-1 score of 0.37291 that is better than those generated by traditional strategy (at 0.36936) on DUC04 task-2.