Research Article
Multi-Document Summarization using CS-ABC Optimization Algorithm
@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
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.
Copyright © 2020 K. Chandra Kumar et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.