FOOD RECOMMENDATION SYSTEM USING MACHINE LEARNING

International Journal of Innovative Research in Technology

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

FOOD RECOMMENDATION SYSTEM USING MACHINE LEARNING
Author(s):
Anil Manmothe, Kanchan Mahajan, Abhijeet Patil, Bhagyashri Patil, Jayashree Mahale
Keywords:
Recommender Systems, Rate Criteria Analysis, Food Recommenders
Abstract
Traditional Recommender Systems recommend items on the basis of a single criterion whereas rates of hotel food take many different criteria for each item. Although rating system of food recommender Systems have a promising accuracy, approaches used by them require many previous users to first rate items with respect to criteria. This paper presents a rating Criteria Recommendation System for food Recommendations to choose the best suited hotel in a city according to a users’ preference and other user’s ratings. In order to determine the food rating of a hotel from previous users uses various Natural Language Processing approaches on a hotel of food review corpus and builds a user-item-feature database. At time of hotel leaving the user give rating for next recommendation, if both user give same rating to one hotel food then and if next time one user can rate to other hotel that hotel will recommend to other user.
Article Details
Unique Paper ID: 149164 Publication Volume & Issue: Volume 6, Issue 11 Page(s): 113 - 117
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