An Enhanced Extraction and Summarization Technique with User Review Data for Product Recommendation to Customers

Authors

  • Vikas B O  Assistant Professor, Department of IS & E, NHCE, Bangalore, India
  • Dr. Jitendranath Mungara  Professor & HOD, Department of IS & E, NHCE, Bangalore, India

Keywords:

Product recommendation, Opinion mining, Sentiment analysis, Natural Language Processing, POS tagging

Abstract

In the current world, recommendation system plays a major role in helping consumer find for relevant product information with summarized reviews. The recommendation system contains collection of opinions, reviews, recommendation, ratings, comment and personal experience shared by different user review on a product through social networks, e-commerce websites, blogs and forums. These reviews become an opinion for consumers to learn different aspects of products like limitations, advantages, features, services and suppliers. Various methods of evaluating products/services to consumer are provided from different review sites. The proposed method extracts reviews and summarises to provide enhanced product recommendation to the consumer.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2016-12-30

Issue

Volume 2, Issue 6, November-December-2016

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Vikas B O, Dr. Jitendranath Mungara "An Enhanced Extraction and Summarization Technique with User Review Data for Product Recommendation to Customers" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 6, pp.25-30, November-December-2016.