


Volume 21 No 6 (2023)
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A NEW AND EFFICIENT SENTIMENT ANALYSIS BASED ON MACHINE LEARNING TECHNIQUES FOR ANALYZING RESTAURANT REVIEWS
ZABI UR RAHAMAN K, Dr. M. GIRI
Abstract
Sentiment analysis increased popularity and it can be used in many applications to analyze performance of a business. Now a day’s everybody using internet that created a path of web is a one of the primary source of data. Large number of web users use different websites to give their opinions on variety of products. We need to automate a system to monitor these reviews on products continuously. In this research paper proposed sentiment analysis based machine learning techniques to analyze restaurant reviews. Proposed method consist of four phases, first phase dataset like Tripadvisor, HotelRec, Datafiniti, Edmunds, Yelpchi, and IndoNLU restaurant reviews for classification. Second phase, collected reviews are preprocessed to count strong words and its frequencies in review documents. Third phase, proposed sentiment analysis based on machine learning techniques, naïve bayes classification method used to classify datasets, and in forth phase discovered outcomes are presented to end user. Performances of proposed algorithm are evaluated by using performance evaluation methods and proposed method classifies data accurately.
Keywords
Sentiment Analysis, Machine Learning, Word frequencies, naïve bayes classification, naïve bayes theorem, restaurant reviews, dataset
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