Cross-document summarization by concept classification
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
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
Syntactic simplification for improving content selection in multi-document summarization
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A web knowledge based approach for complex question answering
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
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In this paper, we propose a method for multi-document summarization based on unsupervised clustering. First, the main topics are determined by a MDL-based clustering strategy capable of inferring optimal cluster numbers. Then, the problem of multi-document summarization is formalized on the clusters using an entropy-based object function.