摘要
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.
原文 | English |
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文章編號 | 5759102 |
頁(從 - 到) | 397-407 |
頁數 | 11 |
期刊 | IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews |
卷 | 42 |
發行號 | 3 |
DOIs | |
出版狀態 | Published - 1 5月 2012 |