Mô hình khai phá quan điểm dựa trên đặc trưng các đánh giá sản phẩm trong tiếng Việt

In this thesis, we present an approach to build an opinion mining system of customer reviews according to product features based on Vietnamese syntax rules and VietSentiWordNet dictionary in four phases: (1)Pre-processing; (2)Extracting explicit/implicit product features and opinion-words,and grouping synonym product features; (3)Identifying orientation of opinion; and (4)Summarizing the results. With three main contributions as following: Firstly, in the phase 1, we build a Vietnamese accented system combined N-gram statistic model and Hidden Markov model(HMM) for the purpose ofconverting a sentence without accents into a Vietnamese accented sentence. Secondly, in the phase 2, we construct a mapping dictionary to identify implicit features by mapping those ones to corresponding opinion words; and we proposed a method of using SVM-kNN semi-supervised learning along with HAC clustering method generating training set for SVM-kNN to group synonym features; after that, co-reference was resolved by using some Vietnamese rules.

http://repository.vnu.edu.vn/handle/VNU_123/8269