1. Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Quality evaluation of product reviews using an information quality framework Presenter : Cheng-Hui Chen Author : Chien Chin Chen, You-De Tseng DSS 2011

2. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 2 Outlines Motivation Objectives Methodology Experiments Conclusions Comments

3. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation  Most opinion mining and retrieval approaches try to extract sentimental or bipolar expressions from a large volume of reviews. the process often ignores the quality of each review and may retrieve useless or even noisy documents. 3

4. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objectives  we propose a method for evaluating the quality of information in product reviews. 4

5. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 5

6. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology  Definition of review quality ─ Five classes of review quality, namely high-quality, medium-quality, low-quality, duplicate and spam. 6

7. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology  Information quality-based review features ─ Believability (D1) ─ Objectivity (D2) ─ Reputation (D3) ─ Relevancy (D4) ─ Timeliness (D5) ─ Completeness (D6) ─ Appropriate Amount of Information (D7) ─ Ease of Understanding (D8) ─ Concise Representation (D9) 7

8. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology  Classification models ─ One-Versus-All SVM (OVA SVM) ─ Single-Machine Multiclass SVM (SMM SVM) 8 OVA SVM High qualityspam SMM SVM High quality Spam Medium quality OVA SVM High qualityspam

9. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Review quality evaluation  Review quality evaluation  Review ranking and retrieval 9

10. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 10

11. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 11

12. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 12

13. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 13

14. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 14

15. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments  High-quality review analysis 15

16. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusions  Our method can accurately classify reviews in terms of their quality, and that it significantly outperforms state-of-the-art methods.  This paper analyze the factors that are important for compiling high-quality reviews and demonstrate that such reviews need to be subjective and provide in- depth comments on a number of product features. 16

17. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Comments  Advantages ─ This paper did a lot of experiments.  Drawback ─ …  Applications ─ Information retrieval. 17