Food Spot: An Intelligent Location-Aware Food Recommendation System Using Machine Learning and NLP-Based Sentiment Analysis on Indian Restaurant Datasets

Tejaswini, Y. Naga; Sandeep, J.; Ganesh, R.; Dinesh, E.

doi:https://doi.org/10.55041/ijcope.v2i4.208

Volume 02, Issue 04

Published on: April 2026

FOOD SPOT: AN INTELLIGENT LOCATION-AWARE FOOD RECOMMENDATION SYSTEM USING MACHINE LEARNING AND NLP-BASED SENTIMENT ANALYSIS ON INDIAN RESTAURANT DATASETS

Y. Naga Tejaswini J. Sandeep R. Ganesh E. Dinesh

K. Sukeerthi

Department of CSE(DataScience) ACE Engineering College Hyderabad Telangana India

DOI:https://doi.org/10.55041/ijcope.v2i4.208

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Abstract

Speedy growth within India's restaurant industry has resulted in much more than many users could navigate when trying to find things to eat they like and that they can afford. Traditional sources of discovering food provide raw data and raw reviews, but do not provide any Intelligent or personalised direction. The authors of this paper are proposing to address these limitations with Food Spot, an intelligent web-based recommendation system for discovering food, using both machine learning techniques and Natural Language Processing (NLP) based sentiment analysis to process all publicly available datasets of Indian restaurant data from Kaggle to allow for the top five most popular dishes occupying any given location in India to be combined with the highest rated restaurant options which fit into the user defined budget.A weighted ranking algorithm will calculate a user's overall dish and restaurant rankings based on the user's food popularity score, corresponding restaurant ratings and customer sentiment polarity from user reviews by calculating a data based recommendation. The system will be made available as a responsive, browser accessible application, with a Flask-Python backend and an HTML structured front end. Initial experimental testing of the operational web application (named Street Byte), was successful in providing users with accurate and almost instantaneous recommendations in multiple cities across India, all recommendations were filtered based on both location and user defined budget..

Keywords—Food Recommendation System, Machine Learning, Sentiment Analysis, Natural Language Processing, Indian Restaurant Dataset, Flask, Web Application, Budget-Based Filtering, Popularity Scoring, Data-Driven Discovery.

How to Cite this Paper

Tejaswini, Y. N., Sandeep, J., Ganesh, R. & Dinesh, E. (2026). Food Spot: An Intelligent Location-Aware Food Recommendation System Using Machine Learning and NLP-Based Sentiment Analysis on Indian Restaurant Datasets. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.208

Tejaswini, Y., et al.. "Food Spot: An Intelligent Location-Aware Food Recommendation System Using Machine Learning and NLP-Based Sentiment Analysis on Indian Restaurant Datasets." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.208.

Tejaswini, Y.,J. Sandeep,R. Ganesh, and E. Dinesh. "Food Spot: An Intelligent Location-Aware Food Recommendation System Using Machine Learning and NLP-Based Sentiment Analysis on Indian Restaurant Datasets." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.208.

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References

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•Published on: Apr 10 2026

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