Machine learning based class level prediction of restaurant reviews

Abstract

Nowadays with the proliferation of location aware technologies and smart phones people tend to give reviews for all types of products services and place them online. It is very important to extract knowledge or information occupies in the vast amount of available text reviews. For these, user's sentiment is also monumental. If any business owners want to take decision on future planning, they must consider their clients sentiment. In this research, we proposed a noble strategy to predict user sentiment from their online reviews given for a particular business by using supervised machine learning techniques. Our proposed machine learning model will give a hand to restaurant owners to identify their customer's feedback and market positions.

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Buildings, Predictive models, Classification algorithms, Business, Training, Social network services, Sentiment analysis

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