Experiments with CST-Based Multidocument Summarization
Maria Lucía Castro Jorge, Thiago Alexandre Salgueiro Pardo · Workshop on Graph Based Methods for Natural Language Processing · 2010
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.