Abstract
Research on recommendation system is now getting a lot of attention due to the rapid growth of user generated contents, especially internet review forums. Users easily share about their experiences towards some products and services on the review forums. As a result, review forums are overwhelmed with the amount of valuable information for predicting user interests. In our work, we present a method to develop a recommendation system leveraging the information mined from review forums. Our method automatically determines user interests by learning from user reviews. Furthermore, we propose the notion of "considered aspects" as the form of user interests, which serve as key information why users are interested in consuming a specific product or service. Several state-of-the-art methods, such as Latent Dirichlet Allocation (LDA), are employed to extract those "considered aspects".
Keywords
Fine-grained sentiment classification
sentiment analysis
online forums
review rating prediction
neural networks
Opinion Shift prediction
Social Media
Natural Language Processing
Word Embedding’s.
Authors
How to Cite this Article
Abhishek J, Mouli J E, Abi Ezhilan, S.Nalini (2017).
"RATING PREDICTION BASED ON SENTIMENTAL ANALYSIS OF REVIEWS FROM ONLINE TRENDING FORUMS".
International Journal of Contemporary Research in Computer Science and Technology,
3(3), pp. 10-14.
