Fiducia: A Personalized Food Recommender System for Zomato

March 25, 2019 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Mansi Goel, Ayush Agarwal, Deepak Thukral, Tanmoy Chakraborty arXiv ID 1903.10117 Category cs.IR: Information Retrieval Cross-listed cs.SI Citations 1 Venue arXiv.org Last Checked 4 months ago
Abstract
This paper presents Fiducia, a food review system involving a pipeline which processes restaurant-related reviews obtained from Zomato (India's largest restaurant search and discovery service). Fiducia is specific to popular cafe food items and manages to identify relevant information pertaining to each item separately in the reviews. It uses a sentiment check on these pieces of text and accordingly suggests an appropriate restaurant for the particular item depending on user-item and item-item similarity. Experimental results show that the sentiment analyzer module of Fiducia achieves an accuracy of over 85% and our final recommender system achieves an RMSE of about 1.01 beating other baselines.
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