OVERVIEW OF VARIOUS OPTIMIZATION TECHNIQUES FOR RECOMMENDATION SYSTEM

Authors

  • Santosh Das

Keywords:

Recommender System, K-means, K-NN, Particle Swarm Optimization

Abstract

Artificial intelligence and data science has opened the doors of possibilities to help users for optimizing their search results. Ultimately, the search engines are working for providing the exact results to the user upon search. Over last 5 years, number of internet user in India have increased rapidly with the better internet speed and verity of android options available in market. At the end of 2020, the number of internet users in India is forecasted as 650 million which will be around 50% of Indian population. With huge number of users, it becomes very important to provide the optimised search results. Matching the preferences of users in search results may increase the user satisfaction. Many web services, applications and search engines use recommender system to enhance the user experience. Authors have presented the overview of various techniques implemented in optimization of search results for the recommender system.

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Published

2021-01-22

Issue

Vol. 7 No. 10 (2020): IJIERT

Section

Articles

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