Rest-Rec: Restaurant Recommender System Based on Model Based Collaborative Filtering Approach
Keywords:
Recommendation system, Restaurant recommender, K-means algorithm, Collaborative filtering.Abstract
Recommendation Engine has become the need for everyone and has changed the lifestyle of people in the aspect of searching products and services. Recommendation systems are used in almost all areas driving from education to entertainment. A recommendation system is a class of information filtering system to provide choices to the users based on their preference. Considering the need and importance of recommendation system, this paper proposed a recommender called Rest-Rec for restaurants based on collaborative filtering approach. Rest-Rec analyses the previous user’s information and recommends the restaurants as per user’s preference. K-Means algorithm is employed to cluster the restaurants based on the rating by the users. Performance of proposed Rest-Rec is evaluated using data from Trip Advisor website in terms of Precision, Recall, F1-Score. It is evident from the results that Rest-Rec provides recommendation with precision of 95.67%.
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