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 abstracting and indexing—survey and recommendations
Communications of the ACM
An information-theoretic approach to automatic evaluation of summaries
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Fast global k-means with similarity functions algorithm
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Editorial: COMPENDIUM: A text summarization system for generating abstracts of research papers
Data & Knowledge Engineering
| Hi-index | 0.00 |
In this paper, we present a novel approach for automatic summarization. Our system, called CBSEAS, integrates a new method to detect redundancy at its very core, and produce more expressive summaries than previous approaches. Moreover, we show that our system is versatile enough to integrate opinion mining techniques, so that it is capable of producing opinion oriented summaries. The very competitive results obtained during the last Text Evaluation Conference (TAC 2008) show that our approach is efficient.