Recommendation System using Clustering and Comparing Clustering and Topic Modelling Techniques
Ekta Sharma, Jibrael Jos · 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022
In this paper, we have used a technique called clustering to recommend the products to the customer and also tried to compare clustering and Topic modelling to find out which technique is better for our purpose. From all the papers that have been reviewed, we observed that the greater part of the proposal approaches applied content-based filtering (55%). Collaborative-based filtering was applied by just 18% of the looked into approaches, and hybrid based by 16%. Other suggestion ideas included generalizing, thing driven proposals, and crossover suggestions. The content-based filtering approaches overwhelmingly utilized papers that the clients had made, marked, examined, or downloaded [1]. To begin with, it stays muddled which suggestion ideas and approaches are the most encouraging. For instance, analysts demonstrated different results on the presentation of content based and collaborative filtering. A portion of the time content-based filtering performed better contrasted with collaborative filtering sand a portion of the time it performed all the more regrettable.