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

Mô hình khai phá quan điểm dựa trên đặc trưng các đánh giá sản phẩm trong tiếng Việt Vũ Tiến Thành Trường Đại học Công nghệ Chuyên ngành: Khoa học máy tính; Mã số: 60 48 01 Người hướng dẫn: PGS.TS. Hà Quang Thụy Năm bảo vệ: 2012 Abstract: 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. Keywords: Khoa học máy tính; Khai phá dữ liệu; Mô hình dữ liệu Table of Contents 1 Introduction 1 2 Literature review 4 2.1 Opinion Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1.1 The demand of opinion mining . . . . . . . . . . . . . . . . . 4 2.1.2 The basic concepts in the opinion mining field . . . . . . . . . 7 2.1.3 Opinion mining problems . . . . . . . . . . . . . . . . . . . . . 9 2.2 Feature-based Opinion Mining . . . . . . . . . . . . . . . . . . . . . . 10 2.2.1 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2.2 Features Extraction . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2.3 Opinion Orientation Identification . . . . . . . . . . . . . . . . 12 2.2.4 Feature-based Opinion Mining System on Vietnamese Product Reviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3 Our Feature-based Opinion Mining Model 15 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2 Phase 1: Pre-processing . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2.1 Data Standardizing . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2.2 Token Segmenting and POS Tagging . . . . . . . . . . . . . . 17 3.3 Phase 2: Product Features and Opinion Words Extraction . . . . . . 18 3.3.1 Explicit Product Features Extraction . . . . . . . . . . . . . . 18 3.3.2 Opinion word Extraction . . . . . . . . . . . . . . . . . . . . . 21 3.3.3 Implicit Features identification . . . . . . . . . . . . . . . . . . 22 3.3.4 Grouping Synonym Features . . . . . . . . . . . . . . . . . . . 23 3.3.5 Frequent Features Identification . . . . . . . . . . . . . . . . . 24 3.4 Phase 3: Determining the opinion orientation . . . . . . . . . . . . . . 26 3.5 Phase 4: Summarization . . . . . . . . . . . . . . . . . . . . . . . . . 28 vi TABLE OF CONTENTS vii 4 Evaluation 29 4.1 Environment and Experimental Data . . . . . . . . . . . . . . . . . . 29 4.1.1 Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 4.1.2 Experimental Data . . . . . . . . . . . . . . . . . . . . . . . . 29 4.2 Product Features Extraction Evaluation . . . . . . . . . . . . . . . . 30 4.3 Opinion Words Extraction Evaluation . . . . . . . . . . . . . . . . . . 31 4.4 The Whole System Evaluation . . . . . . . . . . . . . . . . . . . . . . 32 5 Conclusion 36 Bibliography Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 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Keywords: Khoa học máy tính; Khai phá dữ liệu; Mô hình dữ liệu Table of Contents 1 Introduction 1 2 Literature review 4 2.1 Opinion Mining. Đại học Công nghệ Chuyên ngành: Khoa học máy tính; Mã số: 60 48 01 Người hướng dẫn: PGS.TS. Hà Quang Thụy Năm bảo vệ: 2012 Abstract: In this thesis, we present an approach to build an