1 / 21

Efficient Mining of Recurrent Rules from a Sequence Database

Efficient Mining of Recurrent Rules from a Sequence Database. David Lo Siau -Cheng Khoo Chao Liu DASFAA 2008. Outline. Introduction Preliminaries Generation of Recurrent Rules Algorithm Performance Evaluation Conclusion. Introduction.

devaki
Download Presentation

Efficient Mining of Recurrent Rules from a Sequence Database

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Efficient Mining of Recurrent Rules from a Sequence Database David Lo Siau-Cheng Khoo Chao Liu DASFAA 2008

  2. Outline • Introduction • Preliminaries • Generation of Recurrent Rules • Algorithm • Performance Evaluation • Conclusion

  3. Introduction • Mining for knowledge from data has been shown useful for many purposes ranging from finance, advertising, bio-informatics and recently software engineering. “Whenever a series of precedent events occurs, eventually another series of consequent events occurs”

  4. Introduction 1. Resource Locking Protocol: Whenever a lock is acquired, eventually it is released. 2. Internet Banking: Whenever a connection to a bank server is made and an authentication is completed and money transfer command is issued, eventually money is transferred and a receipt is displayed. 3. Network Protocol: Whenever an HDLC connection is made and an acknowledgement is received, eventually a disconnection message is sent and an acknowledgement is received.

  5. Preliminaries • Linear-time Temporal Logic (LTL) ‘G’ specifies that globally at every point in time a certain property holds. ‘F’ specifies that a property holds either at that point in time or finally (eventually) it holds. ‘X’ specifies that a property holds at the next event.

  6. Preliminaries

  7. Preliminaries • Checking/Verifying LTL Expressions. (main, lock) → (unlock, end) (main, lock, use) → (unlock, end)

  8. Generation of Recurrent Rules Concepts and Definitions

  9. Generation of Recurrent Rules Concepts and Definitions

  10. Generation of Recurrent Rules Concepts and Definitions

  11. Generation of Recurrent Rules Concepts and Definitions

  12. Generation of Recurrent Rules Concepts and Definitions

  13. Generation of Recurrent Rules Concepts and Definitions s-support:2 i-support:2 confidence:1

  14. Generation of Recurrent Rules Concepts and Definitions

  15. Generation of Recurrent Rules Concepts and Definitions s-support:2 i-support:2 confidence:1

  16. Generation of Recurrent Rules Apriori Properties and Non-redundancy

  17. Generation of Recurrent Rules Apriori Properties and Non-redundancy

  18. Generation of Recurrent Rules Apriori Properties and Non-redundancy

  19. Algorithm

  20. Performance Evaluation

  21. Conclusion

More Related