1. Mining Product Opinions and Reviews on The Web Felipe Mattosinho

2. Agenda Introduction Basics Requirements Design Implementation Evaluation Conclusion

3. Introduction

5. retrieve useful information out of users opinions

6. a sub-area of Web Mining

8. Difficult to find necessary information

10. Tiresome task for usersSource: CNET.com

11. Basics

12. Basics Opinion Model Opinions highlight strengths and weaknesses about objects under discussion (OuD) O:(T,A), T is a taxonomy of components and A is a set of attributes of O The use of word feature for simplicity

14. Requirements

15. Requirements Target Audience

17. Fault-tolerance

18. Performance

21. POS Tagging Module

22. Opinion Retriever Module

27. Design Feature Identification camera_NN (picture_NN quality_NN) zoom_NN thing_NN LCD_NNP resolution_NN wedding_NN car_NN photos_NNS dog_NN road_NN lot_NN [...] camera_NN (picture_NN quality_NN) flash_NN thing_NN England_NNP rehearsel_NN photos_NNS [...] horse_NN (picture_NN quality_NN) flash_NN farm_NN country_NN rehearsel_NN photos_NNS [...] camera_NN (picture_NN quality_NN) flash_NN photos_NNS [...]

31. „The camera is nice, except for the initialization time which takes long “

34. Nokogiri

35. Ruby-aaws

38. Implementation Overview

39. Evaluation

41. Ubuntu 9.04 32 bitsSample data System Configuration

42. Evaluation Effectiveness of Feature Identification Threshold Accuracy Features

47. „This camera is GOOD“

49. Conclusion Future Work Minimize number of manual annotations through recognition of reusable patterns of the human language Cope with common unsolved problems such as Safe ways to recognize which features belong to which object Global opinion knowledge to help improvement of local analysis (sentence or feature level)

50. Conclusion Questions?