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- W4311184477 abstract "Restaurants these days like taking web-based orders. It is not just aiding in getting viable client’s feedback but additionally valuable for overseeing orders without any problems. We are moving toward a mechanized and advanced world. Having a huge presence on the web is essential for any restaurant to find true success and prosperity. Getting client’s feedback and examining them in a powerful way has an effect. Furthermore, it presents helpful data that the evaluations do not consider or neglect. Consolidated research is finished utilizing two different datasets of restaurant reviews in this paper. Machine learning calculations like Naïve Bayes and Logistic Regression are utilized for first grouping the surveys into legitimate perspectives and then performing opinion investigation on them. This study investigates restaurant reviews taken from Kaggle and yielding an exactness score of 66.66% for Naive Bayes and 92.22% for Logistic Regression." @default.
- W4311184477 created "2022-12-24" @default.
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- W4311184477 date "2022-12-03" @default.
- W4311184477 modified "2023-09-27" @default.
- W4311184477 title "Sentimental Analysis and Classification of Restaurant Reviews" @default.
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- W4311184477 doi "https://doi.org/10.1007/978-981-19-6004-8_20" @default.
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