Food Recommendation System using Custom NER and Sentimental Analysis

In today's fast-paced lifestyle, the need for efficient and personalized solutions is paramount, especially in the category of dining experiences. This research responds to this demand by proposing a better food recommendation system for Zomato reviews. It targets the audience who are not aware...

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Bibliographic Details
Published in2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies pp. 1 - 6
Main Authors Adab, Aqsa, Jain, Muskan, R., Gunavathi, Bhagat, Vandana, Hussain, Ashaq G, Johnson, Amala
Format Conference Proceeding
LanguageEnglish
Published IEEE 22.03.2024
Subjects
Analytical models
Computational modeling
Food Recommendation System
Fuzzy Strings
Named Entity Recognition(NER)
Pre-trained Roberta based NER model
Quantum computing
Reviews
Sentiment analysis
Sentimental Analysis
TextBlob
Urban areas
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Summary:In today's fast-paced lifestyle, the need for efficient and personalized solutions is paramount, especially in the category of dining experiences. This research responds to this demand by proposing a better food recommendation system for Zomato reviews. It targets the audience who are not aware of the best cuisines and search for user reviews online. Utilizing custom Named Entity Recognition (NER) and sentiment analysis, the system seeks to understand and cater to individual food preferences extracted from user Reviews. Specifically, improving the analysis by extracting reviews for ten restaurants in the city of Kolkata. By providing a specific solution to address the current research gap in the area of restaurants recommendation systems, the system recommends top choices for neighboring restaurants and best food based on the sentimental analysis of the chosen menu items.
DOI:10.1109/TQCEBT59414.2024.10545046