Abstract: Aiming at the problems existing in LDA model used to extract product features, a method combined syntactic analysis and topic model, named SA-LDA, is proposed. Firstly, we analyze reviews under products which belong to a category based on syntactic analysis, extract explicit features and cluster them to get feature set and opinion set, and then construct corpus. After that, opinion sentences are extracted to be used for topic clustering, must-link and cannot-link are constructed for guiding the topic learning and each topic corresponds to a specific feature cluster. Experiments show that the performance of the method proposed in this paper is good in explicit features and implicit features, and it not only ensures recall rate, but also improves precision score compared to other methods.
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Key words: latent Dirichlet allocation, topic model, syntactic analysis, feature extraction, constraint condition