Title: Restricted Boltzmann Machines for Modeling Businesses

Year of Publication: Nov - 2014
Page Numbers: 24-28
Authors: Andreea Salinca
Conference Name: The International Conference on Artificial Intelligence and Pattern Recognition (AIPR2014)
- Malaysia

Abstract:


User-generated business reviews have a significant impact in decision making of consumers. It would be useful to predict if a business is good for children or to predict its ratings using only text reviews. In this paper, an approach on modeling consumers reviews using a probabilistic model, Restricted Boltzmann Machines (RBMs), is proposed. We apply RBMs for non-linear feature extraction on Yelp data set consisting of raw data for businesses. Obtained results using RBMs modeling outperform results using traditional classifiers.