Expert Systems with Applications: An International Journal
Summary extraction from chinese text for data archives of online news
DNIS'11 Proceedings of the 7th international conference on Databases in Networked Information Systems
Cognitive intentionality extraction from discourse with pragmatic-tree construction and analysis
Information Sciences: an International Journal
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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.