참고문헌
- Michael J. A Berry, and Gorden Linoff, Data Mining Techniques : For Marketing, Sales, and Customer Support, John Wiley & Sons, Inc., 1997
- R.Agrawal, T. Imielinski, and A. Swami. 'Mining association rules between sets of items in large databases,' In Proc. of the ACM SIGMOD Conference on Management of Data, pp. 207-216, Washington, D.C., May 1993 https://doi.org/10.1145/170036.170072
- R. Agrawal and R. Srikant, 'Fast algorithms for mining association rules,' In Proc.of the 20th International Conference on Very Large Data Bases (VLDB94), pp. 487-499, Santiage, Chile, September 1994
- Jong Soo Park, Ming Syan Chen and Philip S.Yu, 'Efficient parallel mining for association rules,' In the 4th International Conference on Information and Knowledge Management, pp. 31-36, Baltimore, MD, November 1995 https://doi.org/10.1145/221270.221320
- Rakesh Agrawal and John C. Shafer, 'Parallel Mining of Association Rules,' IEEE Transations on Knowledge and Data Engineering, Vol. 8, No. 6, pp. 962-969, December 1996 https://doi.org/10.1109/69.553164
- D. W. Cheung, J. Han, V. Ng, A. W. Fu and Y.Fu, 'A fast distribution algorithm for mining association rules,' International Conference on Parallel and Distributed Information Systems, Miami Beach, Florida, December 1996
- Jung Soo Park, Ming-Syan Chen, and Philip S. Yu., 'An effective hash-based algorithm for mining association rules,' In Proc. of ACM SIGMOD Conference on Management of Data(SIGMOD'95), pp. 175-186, San Jose, California, May 1995 https://doi.org/10.1145/568271.223813
- Ashok Savasere, Edward Omiecinski, and Shamkant Navathe, 'An effective algorithm for mining association rules in large databases,' In Proc. of the 21st International Conference on Very Large Data Bases (VLDB'95), pp. 432-444, Zurich, Swizerland, 1995
- Hannu Toivonen, 'Sampling Large Database for Association rules,' In Proc. of the 22nd International Conference on Very Large Data Bases (VLDB'96), Mumbai(Bombay), India, 1996
- D. W. Cheung, J. Han, V. Ng and C. Y. Wong, 'Maintenance of discovered association rules in large database : An incremental updating technique,' International Conference on Data Engineering, New Orleans, Louisiana, February 1996
- Sergey Brin, Rajeev Motwani, Jeffrey D. Ulman, and Shalom Tsur., 'Dynamic Itemset Counting and Implication Rules for Market Basket Data,' In Proc. of ACM SIGMOD Conference on Management of Data (SIGMOD'97), pp. 255-264, 1997 https://doi.org/10.1145/253262.253325
- Alexander Hinneburg, Daniel A. Keim, 'Clustering Techniques for Large Data Sets-From the Past to the Future,' In Proc. of ACM SGMOD International Conference on KDD, San Diego, CA, USA, August 1999 https://doi.org/10.1145/312179.312189
- Anders L. Madsen, and Finn V. Jensen, Parallelization of Inference in Bayesian Networks, 1999
- Raymond T. Ng, Jiawei Han, 'Efficient and Effective Clustering Method for Spatial Data Mining,' In Proc. of the VLDB Conference, Santiago, Chile, 20th Int, pp. 144-155, September 1994
- Tian Zhang, Raghu Ramakrishnan, and Miron Livny, 'BIRCH : An Efficient Data Clustering Method for Very Large Databases,' In Proc. of the ACM SIGMOD Conference on Management of Data, Montreal, Canada, pp. 103-114, June 1996 https://doi.org/10.1145/235968.233324
- Martin Ester, Hans-Peter Kriegel, Jorg Sander, and Xiaowei Xu, 'A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise,' In Proc. of ACM SIGMOD 3rd International Conference on Knowledge Discovery and Data Mining, pp. 226-231, AAAI Press, 1996
- Xiaowei Xu, Martin Ester, Hans-Peter Kriegel, and Jorg Sander, 'A Distribution- Based Clustering Algorithm for Mining in Large Spatial Databases,' In proc. of 14th International Conference on Data Engineering(ICDE), Orlando, Florida, USA, pp. 324-331, february 1998 https://doi.org/10.1109/ICDE.1998.655795
- Sudipto Guha, Rajeev Rastogi, and Kyuseok Shim, 'CURE : An Efficient Clustering Algorithm for Large Databases,' In Proc. ot the ACM SIGMOD Conference on Management of Data, Seattle, Washinton, USA, pp. 73-84, May 1998 https://doi.org/10.1145/276304.276312
- Alexander Hinneburg, and Daniel A.Keim, 'An Efficient Approach to Chustering in Large Multimedia Databases with Noise,' In proc. of 4th International Conference of Knowledge Discovery and Data Mining, New York, pp. 58-65, 1998
- Mihael Ankerst, Markus M. Breuning, Hans-Peter Kriegel, and Jorg Sander, 'OPTICS: Ordering Points To Identify the Clustering Structure,' In proc. of ACM SIGMOD International Conference on Management of Data, Philadephia, Pennsylvania, USA, pp. 49-60, June 1999 https://doi.org/10.1145/304182.304187
- Sudipto Guha, Rajeev Rastogi, and Kyuseok Shim, 'ROCK : A Robust Clustering Algorithm for Categorical Attributes,' In proc. of the 15th International Conference on Data Engineering (ICDE), Sydney, Austrialia, March 1999 https://doi.org/10.1109/ICDE.1999.754967
- Minsky, M. and S. Pappert, Perceptrons, Cambridge : MIT Press, 1969
- Specht, D. F., Probobilistic neural networks, Neural Networks, 1990
- Mark J. L. Orr, Introduction to Radial Basis Function Networks, Edinburgh University, 1996
- Kohenen, T, Learning Vector Quantization, Neural Networks, 1988
- Specht, D. F., 'A Generalized Regression Neural Network,' IEEE Transactions on Neural Networks, 1991
- J. P. Bigus, Data Mining with Neural Networks, McGraw-Hill, 1996
- Kohonen, T., Self-Organizing Maps, 2nd Ed., Berlin: Springer-Verlag., 1997
- http://ftp.sas.com/pub/neural/FAQ.html
- J. Shafer, R. Agrawal, and M.Mehta, 'SPRINT: A scalable parallel classifier for data mining,' In proc. of the VLDB Conference, 1996
- J.Gehtke, R. Ramakrishman, and V. Ganti, 'Rainforest - A framework for fast decision tree construction of large datasets,' In proc. of the VLDB Conference, 1996
- R. Rastogi and K. Shim. 'PUBLIC: A decision tree classifier that integrates building and pruning,' In proc. of the VLDB Conference, 1998
- Jhannnes Gehrke, Venkatesh Ganti, and Raghu Ramakrishnan. 'BOAT: Optimistic Decision Tree Construction,' In proc. of the ACM SIGMOD Conference on Management of Data, Philadelphia, 1999 https://doi.org/10.1145/304182.304197
- David Heckerman, A Tutorial on Learning With Bayesian Networks, 1995
- David Heckerman, 'Bayesian Networks for Knowledge Discovery,' in Advances in knowledge discovery and data mining, pp. 273-305, 1996
- David Heckerman, and Michael P. Wellman, 'Bayesian Networks,' CACM Vol. 38, No. 3, 1995
- John H.Holland, Adaptation in natural and artificial systems, Ann Arbor:the University of Michigan Press,1975
- David Beasley,David R.Bull,and Ralph R.Martin 'An Overview of Genetic Algorithms:Part1, Fundamentals,' University Computing,15(2) pp.58-69, Inter-University Committee on Computing, 1993
- David Beasley,David R.Bull and Ralph R.Martin 'An Overviw of Genetic Algorithms:Part2, Research Topics,' University Computing, 15(4) page170-181,1993
- Koza John R, Genetic Programming : On the Programming of computers by means of Natural Selection, Cambridge,MA,MIT Press,1992. http://ailife.santafe.edu/~joke/encore/ www
- Goldberg David.E, korb Bradley,and Deb K.'Messy Genetic Algorithms:Motivation, Analysis and Results,' TCGA Report 90005, May 1995. http://cs.felk.cvut.cz/~xobitko/ga
- Pooja P.Mutalik,Leslie R.Knight,Joe L.Blanton, and Roger L.Wainwright 'Solving Combinational Optimization problems using parallel simulated annealing and parallel genetic algorithms,' ACM 0-89791-502-x/92/00002/ 1031,1992
- H.Muchlenbein,' Parallel Genetic Algorithms, Population Genetics and combinatorial Optimization,' In Proc. of third International Conference on Genetic Algorithms, Morgan Kaufmann publisher,1989
- Pretty,Chrisila B,Michael R Leuze, and john J.Grefenstette,'A Parallel genetic algorithm,' In Proc. of the 2nd International conference on Genetic Algorithms, pp. 155-161,1987
- Kenneth De Jong,and Wiliam Spears, 'Learning Concept Classification Rules Using Genetic Algorithms,' In Proc. of the 12th International Joint Conference on Artificial Intelligence, pp.651-656, Morgan Kaufmann Publisher,1991
- J.Bala, J.Huang, H.Vafaie, K.DeJong and H.Wechsler,' Hybrid Learning Using Genetic Algorithms and Decision Tree for Pattern Classification,' In Proc. ot the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI95), Volume I pp.719-724, August 1995
- James D Kelly,and Lawrence Davis,' Hybridizing the Genetic Algorithms and the K Nearest Neighbors Classification Algorithms,' In Proc.of the 4th International Conference on Genetic Algorithms and their Applications, Morgan Kaufmann Publishers,1991
- S.S.Anand,D.Patterson,J.G.hughes. and D.A.Bell, Discovering Case Knowledge using Data Mining, Northern Ireland knowledge engineering Laboratory, School of Information and software Engineering, University of Ulster.1998
- Eliseo Reategui, John A. Campell, and Shirley Borghetti, 'Using a Neural Network to Learn General Knowledge in a Case-Based System,' Case-Based Reasoning Research and Development, 1995
- John W. Sheppard and Steven L. Salzberg, 'Genetic Algorithms: Bootstrapping Memory-Based Learning with Genetic,' 12th National Conference on Artificial Intelligence, AAAI, Seattle, August 1994
- Simoudis and James S. Miller, 'The Application of CBR to Help Desk Applications,' In Proc. of the DARPA Case-Based Reasoning Workshop, 1991
- Kihong Park and Bob carter, 'On the Effectiveness of Genetic Search in Combinatorial Optimization ' ACM , 1995
- W. D. Penny, and S. J. Roberts, 'Bayesian neural networks for classification: how useful is the evidence framework?,' Neural Networks 12, pp. 877-892, 1999 https://doi.org/10.1016/S0893-6080(99)00040-4
- Peter Cheeseman, John Stutz, Bayesian Classification (AutoClass): Theory and Results, Advances in knowledge discovery and data mining, pp. 153-180, 1996
- Wray Buntine, Graphical Models for Discovering Knowledge, Advances in knowledge discovery and data mining, pp. 59-82, 1996
- Graphical Models for Discovering Knowledge,Advances in Knowledge discovery and data mining Wray Buntine