Automated text summarization and the SUMMARIST system
TIPSTER '98 Proceedings of a workshop on held at Baltimore, Maryland: October 13-15, 1998
Investigating sentence weighting components for automatic summarisation
Information Processing and Management: an International Journal
A semantic-based approach to content abstraction and annotation for content management
Expert Systems with Applications: An International Journal
A complex network approach to text summarization
Information Sciences: an International Journal
Extractive summarization based on event term clustering
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
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Automatic document summarization is a highly interdisciplinary research area related with computer science, multimedia, statistics, as well as cognitive psychology. In this paper, we introduce an intelligent system, the event indexing and summarization (EIS) system, for automatic document summarization, which is based on a cognitive psychology model (the event-indexing model) and the roles and importance of sentences and their syntax in document understanding. The EIS system involves syntactic analysis of sentences, clustering and indexing sentences with five indices from the event-indexing model and extracting the most prominent content by lexical analysis at phrase and clause levels. After thorough implementation and objective evaluations, the system has shown good performance in multiple documents summarization. This system also incorporates special algorithms related with the third person pronoun resolution to extract the true entities that each sentence describes.