Concepts and effectiveness of the cover-coefficient-based clustering methodology for text databases
ACM Transactions on Database Systems (TODS)
Incremental clustering for dynamic information processing
ACM Transactions on Information Systems (TOIS)
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
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
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
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In this paper we present a generic, language independent multi-document summarization system forming extracts using the cover coefficient concept. Cover Coefficient-based Summarizer (CCS) uses similarity between sentences to determine representative sentences. Experiments indicate that CCS is an efficient algorithm that is able to generate quality summaries online.