An Innovative Recommender System for E-Commerce Websites using Natural Language Processing
Sushmita Bose1, Chaitali Choudhary2, Ashok Behra3, Sumit Kumar Sar4
1Sushmita Bose, CSE, BIT, Durg, C.G., India.
2Chaitali Choudhary, CSE, BIT, Durg, C.G., India.
3Ashok Behra, CSE, BIT, Durg, C.G., India.
4Sumit Kumar Sar, CSE, BIT, Durg, C.G., India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 4085-4089 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7168038620/2020©BEIESP | DOI: 10.35940/ijrte.F7168.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A Recommender System has become the go-to application for the internet generation these days. Mono-variate, bi-variate and multi-variate Recommender Systems are available to consumers of various products and services for the last 10 years or so only. In this paper, opinion mining dependent sentiment analysis using NLP tools will be used to recommend products to their purchasers on e-commerce websites. The application can be developed on the Python platform can be commercially used and will be precisely used to people who have to spend money without traditionally touching or feeling the item.
Keywords: Recommender System, Mono-Variate, Bi-Variate, Multi-Variate, Opinion Mining, Sentiment Analysis, NLP Tools, Python.
Scope of the Article: Text Mining.