Movie Rating and Review Summarization in Mobile Environment

作者：Liu Chien Liang^*; Hsaio Wen Hoar; Lee Chia Hoang; Lu Gen Chi; Jou Emery

来源：IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews , 2012, 42(3): 397-407.

DOI：10.1109/TSMCC.2011.2136334

• Feature extraction
• natural language processing (NLP)
• text analysis
• text mining

In this paper, we design and develop a movie-rating and review-summarization system in a mobile environment. The movie-rating information is based on the sentiment-classification result. The condensed descriptions of movie reviews are generated from the feature-based summarization. We propose a novel approach based on latent semantic analysis (LSA) to identify product features. Furthermore, we find away to reduce the size of summary based on the product features obtained from LSA. We consider both sentiment-classification accuracy and system response time to design the system. The rating and review-summarization system can be extended to other product-review domains easily.

• 出版日期2012-5