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A Game Theory Approach for Multi-document Summarization

  • Research Article - Computer Engineering and Computer Science
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Abstract

In today’s era, information has been growing exponentially on the web, due to which extraction of relevant and concise information has become a challenging task. To overcome the above problem, a fundamental tool known as summarization techniques has been used for understanding and organizing such large datasets. Recently, researchers have been devoting a lot of effort to develop semantics-based models, so as to improve summarization performance. In this paper, a versatile and principled game theory-based multi-document summarization framework integrated with Wikipedia ontology is proposed. The framework exploits the submodularity hidden in underlying ontology and is optimized using the proposed improved algorithm, to enhance the summarization performance. Results of the proposed approach were evaluated with the ROUGE evaluation metric for different multi-document summarization tasks against human-generated summaries and it outperformed DUC, TAC competitors, and other competitive methods.

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Authors and Affiliations

  1. Department of Computer Engineering, Jamia Millia Islamia, New Delhi, 25, India

    Amreen Ahmad & Tanvir Ahmad

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  1. Amreen Ahmad
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  2. Tanvir Ahmad
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Correspondence to Amreen Ahmad.

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Ahmad, A., Ahmad, T. A Game Theory Approach for Multi-document Summarization. Arab J Sci Eng 44, 3655–3667 (2019). https://doi.org/10.1007/s13369-018-3619-y

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