Mining progressive confident rules

ABSTRACT

Many real world objects have states that change over time. By tracking the state sequences of these objects, we can study their behavior and take preventive measures before they reach some undesirable states. In this paper, we propose a new kind of pattern called progressive confident rules to describe sequences of states with an increasing confidence that lead to a particular end state. We give a formal definition of progressive confident rules and their concise set. We devise pruning strategies to reduce the enormous search space. Experiment result shows that the proposed algorithm is efficient and scalable. We also demonstrate the application of progressive confident rules in classification.

REFERENCES

• 1: Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
• 2: Rakesh Agrawal , Ramakrishnan Srikant, Mining Sequential Patterns, Proceedings of the Eleventh International Conference on Data Engineering, p.3-14, March 06-10, 1995
• 3: Ramakrishnan Srikant , Rakesh Agrawal, Mining Sequential Patterns: Generalizations and Performance Improvements, Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology, p.3-17, March 25-29, 1996
• 4: Mohammed J. Zaki, Efficient enumeration of frequent sequences, Proceedings of the seventh international conference on Information and knowledge management, p.68-75, November 02-07, 1998, Bethesda, Maryland, United States [doi>10.1145/288627.288643]
• 5: Minos N. Garofalakis , Rajeev Rastogi , Kyuseok Shim, SPIRIT: Sequential Pattern Mining with Regular Expression Constraints, Proceedings of the 25th International Conference on Very Large Data Bases, p.223-234, September 07-10, 1999
• 6: Jian Pei , Jiawei Han , Behzad Mortazavi-Asl , Helen Pinto , Qiming Chen , Umeshwar Dayal , Meichun Hsu, PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth, Proceedings of the 17th International Conference on Data Engineering, p.215-224, April 02-06, 2001
• 7: Jian Pei , Jiawei Han , Wei Wang, Mining sequential patterns with constraints in large databases, Proceedings of the eleventh international conference on Information and knowledge management, November 04-09, 2002, McLean, Virginia, USA [doi>10.1145/584792.584799]
• 8: M. Zhang and W. Hsu and M. L. Lee, Mining Progressive Confident Rules, Dept. of Computer Science, National University of Singapore, 2006, June, TRA6/06

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

General Terms:
Algorithms, Experimentation, Performance

Keywords:
classification, progressive confident, sequence