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Multi - Category & Multi - Criteria Recommendation System using Collaborative Based Filtering

Journal: International Journal of Science and Research (IJSR) (Vol.10, No. 8)

Publication Date:

Authors : ; ; ; ; ;

Page : 1076-1080

Keywords : Multi Criteria Recommender System (MCRS); K - Nearest Neighbor Algorithm (KNN); Similarity Score; Collaborative - based filtering algorithm;

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Recommendations Systems have become one of the most popular application of data science today. It predicts or offers products to customers based on their past browsing history or purchases. Although a lot of effort, research and time has been spent on recommendation engines, we are yet to truly unlock their potential. At the core, a recommender system employs a machine learning algorithm whose job is to predict user's ratings for a particular entity. Through this project, we are employing a multi category recommendation system which will give the user recommendations across different categories based on the user data of multiple categories consisting of different attributes. The concept of K - Nearest Neighbor Algorithm is implemented to derive the similarity of unknown entities or users based on past ratings of a particular entity. The implementation is carried out using JavaScript in Node, thereby extending the capabilities of Collaborative based filtering Algorithm to multiple categories.

Last modified: 2022-02-15 18:36:48