1. S Fienberg,G Shmueli (2005). Statistical issues and challenges associated with rapid detection of bioterrorist attacks. Statistics in Medicine
2. Pedro Carmona-Saez,Monica Chagoyen,Andres Rodriguez,Oswaldo Trelles,Jose Carazo,Alberto Pascual-Montano (2006). Integrated analysis of gene expression by association rules discovery. BMC Bioinformatics, 7(1)
3. Ronaldo Cristiano,Prati (2009). QROC: A Variation of ROC Space to Analyze Item Set Costs/Benefits in Association Rules. Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction, 133-148.
4. P Mcnicholas (2007). Association rule analysis of CAO data (with discussion). Journal of the Statistical and Social Inquiry Society of Ireland
5. R Prati,P Flach (2005). ROCCER: an algorithm for rule learning based on ROC analysis. Proceeding of the 19th International Joint Conference on Artificial Intelligence
6. Tom Fawcett (2008). PRIE: a system for generating rulelists to maximize ROC performance. Data Mining and Knowledge Discovery, 17(2), 207-224.
7. Hiroyuki Kawano,Minoru Kawahara (2002). Extended Association Algorithm Based on ROC Analysis for Visual Information Navigator.
8. G Piatetsky-Shapiro,G Piatetsky-Shapiro,W Frawley,S Brin,R Motwani,J Ullman (2005). Discovery, Analysis, and Presentation of Strong Rules. Proceedings of the 11th international symposium on Applied Stochastic Models and Data Analysis ASMDA, 16, 191-200.
9. B Liu,W Hsu,Y Ma (1999). Pruning and summarizing the discovered associations. Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, 125-134.
10. Hacene Cherfi,Amedeo Napoli,Yannick Toussaint (2009). A Conformity Measure Using Background Knowledge for Association Rules: Application to Text Mining. Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction, 100-115.
11. B Liu,W Hsu,Y Ma (1999). Pruning and summarizing the discovered associations. Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
12. Hetal Thakkar,Barzan Mozafari,Carlo Zaniolo (2009). Continuous Post-Mining of Association Rules in a Data Stream Management System. Post-Mining of Association Rules, 116-132.
13. P Kuntz,F Guillet,R Lehn,H Briand (2000). A User-Driven Process for Mining Association Rules. 4th Eur. Conf. on Principles of Data Mining and Knowledge Discovery
14. Huawen Liu,Jigui Sun,Huijie Zhang (2009). Post-Processing for Rule Reduction Using Closed Set. Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction, 81-99.
15. Szymon Jaroszewicz,Dan Simovici (2004). Interestingness of frequent itemsets using Bayesian networks as background knowledge. Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, 178-186.
16. S Jaroszewicz,T Scheffer (2005). Fast Discovery of Unexpected Patterns in Data, Relative to a Bayesian Network. ACM SIGKDD Conference on Knowledge Discovery in Databases
17. C Faure,D Delprat,J Boulicaut,A Mille (2006). Iterative Bayesian Network Implementation by using Annotated Association Rules. 15th Int'l Conf. on Knowledge Engineering and Knowledge Management -Managing Knowledge in a World of Networks, 18.
18. B Liu,W Hsu (1996). Post-Analysis of Learned Rules. AAAI/IAAI
19. B Lent,A Swami,J Widom (1997). Mining for strong negative associations in a large database of customer transactions. Proceedings of the Thirteenth International Conference on Data Engineering
20. Sugato Basu,Raymond Mooney,Krupakar Pasupuleti,Joydeep Ghosh (2001). Evaluating the novelty of text-mined rules using lexical knowledge. Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 233-238.
21. Claudia Marinica,Fabrice Guillet (2010). Knowledge-Based Interactive Postmining of Association Rules Using Ontologies. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 22(6)
22. M Zaki,C Hsiao (2002). Charm: An Efficient Algorithm for Closed Itemset Mining. Proc. Second SIAM Int'l Conf. Data Mining, 34-43.
23. J Pei,J Han,R Mao (2000). Closet: An Efficient Algorithm for Mining Frequent Closed Itemsets. Proc. ACM SIGMOD Workshop Research Issues in Data Mining and Knowledge Discovery, 21-30.
24. Mohammed Zaki,Srinivasan Parthasarathy,Mitsunori Ogihara,Wei Li (1998). Parallel Algorithms for Discovery of Association Rules. Data Mining and Knowledge Discovery, 1(4), 343-373.
25. D Burdick,M Calimlim,J Flannick,J Gehrke,T Yiu (2005). Mafia: A Maximal Frequent Itemset Algorithm. IEEE Trans. Knowledge and Data Eng, 17(11), 1490-1504.
26. J Li (2006). On Optimal Rule Discovery. IEEE Trans. Knowledge and Data Eng, 18(4), 460-471.
27. M Hahsler,C Buchta,K Hornik (2008). Selective Association Rule Generation. Computational Statistic, 23(2), 303-315.
28. H Toivonen,M Klemettinen,P Ronkainen,K Hatonen,H Mannila (1995). Pruning and Grouping of Discovered Association Rules. Proc. ECML-95 Workshop Statistics, Machine Learning, and Knowledge Discovery in Databases, 47-52.
29. Roberto Bayardo,Rakesh Agrawal (1999). Mining the most interesting rules. Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, 145-154.
30. M Klemettinen,H Mannila,P Ronkainen,H Toivonen,A Verkamo (1994). Finding Interesting Rules from Large Sets of Discovered Association Rules. Proc. Int'l Conf. Information and Knowledge Management (CIKM), 401-407.
31. R Srikant,R (1995). Mining Generalized Association Rules. Proc. 21st Int'l Conf. Very Large Databases, 407-419.
32. Barzan Mozafari,Hetal Thakkar,Carlo Zaniolo (2008). Verifying and Mining Frequent Patterns from Large Windows over Data Streams. Proceedings of the 24th International Conference on Data Engineering (ICDE 2008)
33. Parallel Edge Projection and Pruning (PEPP) Based Sequence Graph protrude approach for Closed Itemset Mining kalli Srinivasa Nageswara Prasad. Parallel Edge Projection and Pruning (PEPP) Based Sequence Graph protrude approach for Closed Itemset Mining kalli Srinivasa Nageswara Prasad
34. S Prof,Ramakrishna (2011). Unknown Title. International Journal of Computer Science and Information Security Publication, 9(9)
35. Kalli Srinivasa,Nageswara Prasad,Prof Ramakrishna (2011). Global Journal of Computer Science and Technology. Global Journal of Computer Science and Technology, 11(19)
