Experiments with CST-based multidocument summarization

Authors:
Maria Lucía del Rosario Castro Jorge;Thiago Alexandre Salgueiro Pardo
Affiliations:
Universidade de São Paulo, São Carlos/SP, Brazil;Universidade de São Paulo, São Carlos/SP, Brazil
Venue:
TextGraphs-5 Proceedings of the 2010 Workshop on Graph-based Methods for Natural Language Processing
Year:
2010

Citing 11
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Abstract

Recently, with the huge amount of growing information in the web and the little available time to read and process all this information, automatic summaries have become very important resources. In this work, we evaluate deep content selection methods for multidocument summarization based on the CST model (Cross-document Structure Theory). Our methods consider summarization preferences and focus on the overall main problems of multidocument treatment: redundancy, complementarity, and contradiction among different information sources. We also evaluate the impact of the CST model over superficial summarization systems. Our results show that the use of CST model helps to improve informativeness and quality in automatic summaries.