Ensemble based Parallel k means using Map Reduce for Aspect Based Summarization
V. Banu Priya, K. Umamaheswari · 2016
Aspect based summarization is very useful for all the stake holders in analysing voluminous reviews in the web. Even though many parallel algorithms had been available for text summarization, they could not be explicitly used for generating aspect based summaries in the field of opinion mining. In this paper, we have proposed a new parallel k means clustering approach based on Map Reduce framework for aspect based summary generation, which particularly incorporates bagging and ensembling techniques. The performance of the system generated summary is evaluated using ROUGE tool kit with human standard reference summaries and it was found to improve considerably than other state of art approaches.