Food Recommendation System using Custom NER and Sentimental Analysis
Food Recommendation System; Fuzzy Strings; Named Entity Recognition(NER); Pre-trained Roberta based NER model; Sentimental Analysis; TextBlob
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. 2024 IEEE.
Adab A.; Jain M.; Gunavathi R.; Bhagat V.; Hussain A.G.; Johnson A.
TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024
Institute of Electrical and Electronics Engineers Inc.
Adab A., Christ Deemed to Be University, Dept. of Data Science, Lavasa, India; Jain M., Christ Deemed to Be University, Dept. of Data Science, Lavasa, India; Gunavathi R., Christ Deemed to Be University, Dept. of Data Science, Lavasa, India; Bhagat V., Christ Deemed to Be University, Dept. of Data Science, Lavasa, India; Hussain A.G., Christ Deemed to Be University, Dept. of Data Science, Lavasa, India; Johnson A., Christ Deemed to Be University, Dept. of Data Science, Lavasa, India