Fiducia: A Personalized Food Recommender System for Zomato
March 25, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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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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