A Cognitive Interactive Framework for Multi-Document Summarizer

  • Anupam SrivastavaEmail author
  • Divij Vaidya
  • Malay Singh
  • Pranjal Singh
  • U. S. Tiwary
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 179)


In this paper, we present a generic interactive framework based on human cognition, where the system can learn continuously from the Internet and from its interaction with the users. To show the utilization of this framework, Iintelli, an agent based application for multiple text document summarization is developed and compared with the MEAD on the Cran Data Set. Mead is a natural language processing-based summarizer, which provides summary by extracting sentences from a cluster of related documents and Cran is a data set maintained by Information Retrieval Group at University of Glasgow. The human knowledge and experience are represented through fuzzy logic-based word-mesh and sentence-mesh, which can learn. Learning is performed using the competitive models, namely, Maxnet and Mexican Hat Models. As the result shows, the framework performs well as a multi-document summarizer. Though we have tested the framework for multi-document summarization, we believe that it can be extended to develop interactive applications for other domains and tasks.


Short Term Memory Fuzzy Number Competitive Learning Text Summarization Percentage Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Anupam Srivastava
    • 1
    Email author
  • Divij Vaidya
    • 1
  • Malay Singh
    • 1
  • Pranjal Singh
    • 1
  • U. S. Tiwary
    • 1
  1. 1.Indian Institute of Information TechnologyAllahabadIndia

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