ew 20(28): e9

Research Article

Multi-Document Summarization using CS-ABC Optimization Algorithm

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  • @ARTICLE{10.4108/eai.13-7-2018.163835,
        author={K. Chandra Kumar and Sudhakar Nagalla},
        title={Multi-Document Summarization using CS-ABC Optimization Algorithm},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={7},
        number={28},
        publisher={EAI},
        journal_a={EW},
        year={2020},
        month={3},
        keywords={},
        doi={10.4108/eai.13-7-2018.163835}
    }
    
  • K. Chandra Kumar
    Sudhakar Nagalla
    Year: 2020
    Multi-Document Summarization using CS-ABC Optimization Algorithm
    EW
    EAI
    DOI: 10.4108/eai.13-7-2018.163835
K. Chandra Kumar1,2,*, Sudhakar Nagalla3
  • 1: Research scholar in Acharya Nagarjuna University, India
  • 2: Lecturer at the Faculty of Computer Science, Kakinada Institute of Engineering and Technology, India
  • 3: Principal, Bapatla Engineering College, India
*Contact email: chandrakumark2381@gmail.com

Abstract

In revolve handle to the information excess, the dramatic boost up documents, on the WWW, show the way of the accessibility of various credentials through the equal subject with conception. Within a limited time, a hard to inquire a suitable a particular document associated to a specific topic to fulfils user’s compound data conditions. Hence, we have followed an effective document summarization system applying SVM classifier strategy by this paper. For choosing optimal sentence sets, the proposed technique applies the hybrid ABC-CS optimization algorithm. Further, established on few relevant features, SVM classifier approach is applied in finding the summary by ranking each of the optimal sentences. The operational proposal of JAVA and the results were examined for the methodology is implemented.