Distributed Recommender Systems with Sentiment Analysis
Yeliz Yengi, Sevinç İlhan Omurca · Kocaeli Üniversitesi - AVESİS · 2016
In this research rating based recommender system (RS) on sentiment analysis (SA) by using online reviews data by store big data technology. Online reviews are important to understand users decide to buy a product, see a movie or buy a food user feedback. However nowadays collect lots of reviews from user feedback on e-commerce web sites therefore the importance of increasing big data technology, at the same time increasing needs of big calculation. We report on our classification effort on the sentiment information of reviews, structure of distributed file system and frameworks. Our work focuses on information from reviews to improving recommendation accuracy with the big data era.