Indian Journal of Computer Science

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Recommender System in E-Commerce : Bringing Revolution in Marine Product Industry


Affiliations
1 Senior Faculty, Manipal Academy of Higher Education – South Bangalore Campus (Manipal ProLearn – Data Science), Manipal ProLearn, 3rd Floor, Salarpuria Symphony, 7, Service Road, Pragathi Nagar, Electronic City, Bangalore, Karnataka - 560100, India
2 101/B Bakul Bagan Road, Kolkata - 700025, West Bengal, India

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E-commerce business world is evolving at a fast pace and to remain relevant in the business, the ecommerce world started introducing new tools for enhancing customer experience. Recommender System is one such tool. This paper discusses how Recommender system works and major types of Recommender systems which are currently in use. This paper also discusses some applications of the Recommender system in the marine product industry.

Keywords

Collaborative-filtering, Content-based Filtering, e-Commerce, Recommender System

No Classification

Publishing Chronology: Manuscript received July 5, 2018; revised July 25, 2018; accepted July 27, 2018. Date of publication September 6, 2018

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  • Recommender System in E-Commerce : Bringing Revolution in Marine Product Industry

Abstract Views: 169  |  PDF Views: 0

Authors

Subhabaha Pal
Senior Faculty, Manipal Academy of Higher Education – South Bangalore Campus (Manipal ProLearn – Data Science), Manipal ProLearn, 3rd Floor, Salarpuria Symphony, 7, Service Road, Pragathi Nagar, Electronic City, Bangalore, Karnataka - 560100, India
Satyabrata Pal
101/B Bakul Bagan Road, Kolkata - 700025, West Bengal, India

Abstract


E-commerce business world is evolving at a fast pace and to remain relevant in the business, the ecommerce world started introducing new tools for enhancing customer experience. Recommender System is one such tool. This paper discusses how Recommender system works and major types of Recommender systems which are currently in use. This paper also discusses some applications of the Recommender system in the marine product industry.

Keywords


Collaborative-filtering, Content-based Filtering, e-Commerce, Recommender System

No Classification

Publishing Chronology: Manuscript received July 5, 2018; revised July 25, 2018; accepted July 27, 2018. Date of publication September 6, 2018




DOI: https://doi.org/10.17010/ijcs%2F2018%2Fv3%2Fi5%2F138776