Movie rating and review summarization in mobile environment

Chien-Liang Liu*, Wen Hoar Hsaio, Chia-Hoang Lee, Gen Chi Lu, Emery Jou

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

106 Scopus citations


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 a way 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.

Original languageEnglish
Article number5759102
Pages (from-to)397-407
Number of pages11
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Issue number3
StatePublished - May 2012


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


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