1. Intelligent Database Systems Lab N.Y.U.S.T. I. M. A method of extracting malicious expressions in bulletin board systems by using context analysis Presenter: Jun-Yi Wu Authors: Hiroshi Hanafusa, Kazuhiro Morita, Masao Fuketa, Jun-ichi Aoe 2011 IPM 國立雲林科技大學 National Yunlin University of Science and Technology

2. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Outline Motivation Objective Methodology Experiments Conclusion Comments 2

3. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation 3 The extracting scheme of the traditional method depends on words or a sequence of words without considering contexts of articles. To takes a lot of human efforts to alert malicious articles. Malicious expression text Non-malicious expression text

4. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objective To presents a new context filtering algorithm to reduce the effort of human and to improve the rate of false positive without degrading the rate of false negative. 4

5. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 5 The presented system Rule-based extracting knowledge Multi-attribute matching

6. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 6 The presented system

7. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 7 The presented system The outline of context analysis Malicious expression text Non-malicious expression text

8. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 8 The presented system Inadequate and crime expressions InadequateCrime Abuse 、 Discrimination 、 Dating Service Website 、 Obscenity Murder&Violence 、 Explosion&Arson 、 Crime Material 、 Drug

9. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 9 Rule-based extracting knowledge Definition of multi-attribute rules For example : “He kills someone” STR: string, or, word spelling. CAT: category by general concepts, or a part of speeches. SEM: sematic information

10. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 10 Multi-attribute matching Construction of machines(MAPM) Goto and out function

11. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 11 Multi-attribute matching Procedure For example : “I get a strong sward”

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 15 Time evaluation and error analysis

16. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusion 16 The presented method MULTI is a very useful approach for filtering services for inadequate expressions. It is difficult task to register new words and expressions into dictionaries together with their categories and semantics. The rules bases of the presented method MULTI is building for frequent expressions step by step, but there are difficult problems as shown in the following examples: ‘‘RQJmcf2O” kill ‘‘Aaaaqqqbbb”

17. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Comments 17 Advantage  Many examples Drawback  Some mistakes Application  Information retrieval  Context analysis