Evolutionary DBN for the Customers' Sentiment Classification with Incremental Rules

摘要

An increasing number of reviews from the customers have been available online. Thus, sentiment classification for such reviews has attracted more and more attention from the natural language processing (NLP) community. Related literature has shown that sentiment analysis can benefit from Deep Belief Networks (DBN). However, determining the structure of the deep network and improving its performance still remains an open question. In this paper, we propose a sophisticated algorithm based on fuzzy mathematics and genetic algorithm, called evolutionary fuzzy deep belief networks with incremental rules (EFDBNI). We evaluate our proposal using empirical data sets that are dedicated for sentiment classification. The results show that EFDBNI brings out significant improvement over existing methods.