Multi-Document Summarization Using K-Medoids Clustering Approach
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 2
Abstract
Multi document summarization is the process of transforming a set of documents into a single summarized document. The summarized document can give overall idea of the document collection. Summarization of text document involves intensive text processing and computations to generate the summary. Multi document summarization uses topic modeling and clustering based approach for summarizing the large text collection over MapReduce framework. Most of the systems use k-means clustering algorithm for summarization process. Summarizing large volume of text is a challenging and time consuming problem. In order to overcome the problem of time consumption and to improve the accuracy of the summarized document, Kmedoids clustering algorithm is used.
Authors and Affiliations
Dharani Dharan A C, Rahul Prakash S S, Kiruthika S
Keywords
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- EP ID EP23184
- DOI http://doi.org/10.22214/ijraset.2017.2096
- Views 255
- Downloads 7
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