Distribution discovery: Local analysis of temporal rules

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2336, Issue , 2002, Pages 469-480

  Jin, Xiaoming ^a   Lu, Yuchang ^a   Shi, Chunyi ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

INCREMENTAL ALGORITHM; LOCAL ANALYSIS; MINING PROBLEMS; REAL APPLICATIONS; SYNTHETIC DATA; TEMPORAL RULES; TEMPORAL SEQUENCES; TIME DURATION;

DATA MINING;

EID: 84945255683     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-47887-6_47     Document Type: Conference Paper

References (16)

1. M. Klemettinen, H. Mannila, P. Ronkainen, H. Toivonen, and A. I. Verkamo. Finding inter­esting rules from large sets of discovered association rules. The 3rd International Confer­ence on Information and Knowledge Management, pages 401-407, 1994.
2. T. Dietterich, R. Michalski. Discovering patterns in sequences of events. Artificial Intelli­gence, Vol.25, 1985.
3. R. Agrawal, R. Srikant. Mining sequential patterns. International Conference On Data Engi­neering. Taipei, 1995.
4. R. Srikant, R. Agrawal. Mining sequential patterns: generalizations and performance im­provements. The Fifth International Conference on Extending Database Technology, 1996.
5. S. Ramaswamy, S. Mahajan, A. Silberschatz. On the discovery of interesting patterns in association rules, The VLDB Journal, pages 368-379,1998
6. H. Mannila, H. Toivonen, and A.I. Verkamo. Discovering frequent episodes in sequences. The 1st International Conference on Knowledge Discovery and Data Mining, Canada. 1995.
7. P. Kam, A. Fu. Discovering temporal patterns for interval-based events. The 2nd Interna­tional Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000). 2000.
8. Y. Li, X. Wang and S. Jajodia. Discovering temporal patterns in multiple granularities. Inter­national Workshop on Temporal, Spatial and Spatio-Temporal Data Mining. Lyon, France. 2000.
9. X. Chen, I. Petrounias. An Integrated query and mining system for temporal association rules. The 2nd International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000), London, UK. 327-336 2000.
10. G. Das, K. Lin, H. Mannila, G. Renganathan, P. Smyth. Rule discovery from time series, the 4th International Conference on KDD. 1998.
11. M. Spiliopoulou, J.F. Roddick. Higher order mining: modelling and mining the results of knowledge discovery. Data Mining II - Second International Conference on Data Mining Methods and Databases. 2000.
12. U. Fayyad, G. Piatetsky-Shapiro, P. Smyth. From data mining to knowledge discover: and overview. Advances in Knowledge Discovery and Data Mining. 1996.
13. H. Mannila, H. Toivonen. Discovering generalised episodes using minimal occurences. The 2nd International Conference on Knowledge Discovery and Data Mining (KDD-96). 1996.
14. J. Roddick, M. Spiliopoulou. A bibliography of temporal, spatial and spatio-temporal data mining research. SIGKDD Explorations, Vol l, No. 1. 1999.
15. V. Guralnik, J. Srivastava. Event detection from time series data. The 5th International Conference on Knowledge Discovery and Data Mining, USA. 1999.
16. A. Tansel, N. Ayan. Discovery of association rules in temporal databases. 4th International Conference on Knowledge Discovery and Data Mining (KDD'98) Distributed Data Mining Workshop, NewYork, USA, August 1998.