An Ontology- Based Multi-Document Summarization in Apocalypse Management

Abstract

With the problem of extended information resources and the remarkable evaluate of data removal, the require of having automated summarization techniques revealed up. As summarization is needed the most at present searching information on the internet, where the user moves for a specific space of passion as per his question, area centered on summaries would provide the best. Ontology based summarization system for is provided. The ontology is a subjective model, which gives the important framework for semantic representation of textual data. In our suggested system implement the hierarchical levels of ontology to even more enhance the high summary and to execute hierarchical text classification in the field of earth quake management. We signify a scientific study of different techniques in which ontology has been applied for summarization practice. Comprehensive experiments on a selection of press launch appropriate to 2011 Sikkim earth quake illustrate that ontology centered multiple documents summarization techniques outperforms other baselines with regards to the conclusion top quality. Also we are designing a Hierarchical clustering algorithm instead of K-means clustering algorithm for better precision. It is found that the greater part of the current techniques often focus on sentence scoring and less attention is given to the appropriate information content in various records.

Authors and Affiliations

Smita Bachal| Dept. of Computer Engineering Dnyanganga College of Engg. and Research Pune- 411041, India Email:smitabachal@yahoo.com, Mr. S. M. Sangve| Dept. of Computer Engineering Dnyanganga College of Engg. and Research Pune- 411041, India Email:sunil.sangve@zealeducation.com

Keywords

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  • EP ID EP16511
  • DOI -
  • Views 343
  • Downloads 10

How To Cite

Smita Bachal, Mr. S. M. Sangve (2015). An Ontology- Based Multi-Document Summarization in Apocalypse Management. International Journal of Science Engineering and Advance Technology, 3(7), 257-263. https://europub.co.uk/articles/-A-16511