Abstract
The relevance of fuzzy logic, artificial neural networks, genetic algorithms, and rough sets to pattern recognition problems is described through examples. Different integrations of these soft computing tools are illustrated. The significance of the soft computing approach in data mining, knowledge discovery, and Web mining is discussed. Various existing algorithms and tools in this regard are reviewed. Finally, some research challenges and the scope of future research are outlined.
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References
D. Alahakoon, S.K. Halgamuge, B. Srinivasan: Dynamic self organizing maps with controlled growth for knowledge discovery. IEEE Transactions on Neural Networks, 11, 601–614 (2000)
W.H. Au, K.C.C. Chan: An effective algorithm for discovering fuzzy rules in relational databases. In: Proceedings of IEEE International Conference on Fuzzy Systems FUZZ IEEE 98 ( Alaska, May 1998 ) pp. 1314–1319
M. Banerjee, S. Mitra, S.K. Pal: Rough fuzzy MLP: Knowledge encoding and classification. IEEE Transactions on Neural Networks, 9 (6), 1203–1216 (1998)
S. Bengio, Y. Bengio: Taking on the curse of dimensionality in joint distribution using neural networks. IEEE Transactions on Neural Networks, 11, 550–557 (2000)
Y. Bengio, J.M. Buhmann, M. Embrechts, J.M. Zurada: Introduction to the special issue on neural networks for data mining and knowledge discovery. IEEE Transactions on Neural Networks, 11, 545–549 (2000)
J.C. Bezdek, S.K. Pal (eds.): Fuzzy Models for Pattern Recognition: Methods that Search for Structures in Data ( IEEE Press, New York, 1992 )
D. Bikel, R. Schwartz, R. Weischedel: An algorithm that learns what’s in a name. Machine learning, 34 (Special issue on Natural Language Learning)(1/3), 211–231 (1999)
P. Bosc, O. Pivert, L. Ughetto: Database mining for the discovery of extended functional dependencies. In: Proceedings of NAFIPS 99 ( New York, USA, June 1999 ) pp. 580–584
M. Boughanem, C. Chrisment, J. Mothe, C.S. Dupuy, L. Tamine; Connection-ist and genetic approaches for information retrieval. In: F. Crestani, G. Pasi (eds.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ) 50, pp. 102–121.
M. Boughanem, T. Dkaki, J. Mothe, C. Soule-Dupuy: Mercure at trec7. In: Proceedings of the 7th International Conference on Text Retrieval, TREC7 ( Gaithrsburg, MD, 1998 )
S. Brin, L. Page: The anatomy of a large scale hypertextual web search engine. In: Proceedings of Eighth International WWW Conference ( Brisbane, Australia, April 1998 ) pp. 107–117
H. Chen, M. Ramsay, P. Li: The Java search agent workshop. In: F.Crestani, G.Pasi (eds.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ) 50, pp. 122–140
D.A. Chiang, L.R. Chow, Y.F. Wang: Mining time series data by a fuzzy linguistic summary system. Fuzzy Sets and Systems, 112, 419–432 (2000)
V. Ciesielski, G. Palstra: Using a hybrid neural/expert system for database mining in market survey data. In: Proc. Second International Conference on Knowledge Discovery and Data Mining (KDD-96) (Portland, OR, August 2–4, 1996 AAAI Press) pp. 38
K.J. Cios, W. Pedrycz, R. Swiniarski: Data Mining Methods for Knowledge Discovery ( Kluwer, Dordrecht, 1998 )
F. Crestani, G. Pasi, (eds.): Soft Computing in Information Retrieval: Techniques and Application ( Physica-Verlag, Heidelberg, 2000 )
C. Drummond, D. Ionescu, R. Holte: A learning agent that assists the browsing of software libraries. Technical Report TR-95-12 (University of Ottawa, 1995 )
R.O. Duda, P.E. Hart: Pattern Classification and Scene Analysis ( John Wiley, New York, 1973 )
O. Etzioni: The World Wide Web: Quagmire or gold mine. Communications of the ACM, 39 (11), 65–68 (1996)
O. Etzioni, M. Perkowitz: Adaptive web sites: An AI challenge. In: Proceedings of Fifteenth National Conference on Artificial Intelligence ( Madison, Wisconsin, July 1998 )
O. Etzioni, O. Zamir• Web document clustering: A feasibility demonstration. In: Proceedings of the 21st Annual International ACM SIGIR Conference, 1998 pp. 46–54
U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, R. Uthurusamy (eds.): Advances in Knowledge Discovery and Data Mining ( AAAI/MIT Press, Menlo Park, CA, 1996 )
I.W. Flockhart, N.J. Radcliffe: A genetic algorithm-based approach to data mining. In: The Second International Conference on Knowledge Discovery and Data Mining (KDD-96) (Portland, OR, August 2-4 1996 AAAI Press) pp. 299
D. Freitag, N. Kushmerick: Boosted wrapper induction. In: Proceedings of AAAI, 2000 pp. 577–583
D. Freitag, A. McCallum: Information extraction from HMM’s and shrinkage. In: Proceedings of AAAI-99 Workshop on Machine Learning for Information Extraction ( Orlando, FL, 1999 )
H. Fukuda, E.L.P. Passos, A.M. Pacheco, L.B. Neto, J. Valerio, V.Jr.De Roberto, E.R. Antonio, L. Chigener: Web text mining using a hybrid system. In: Proceedings of the Sixth Brazilian Symposium on Neural Networks, 2000 pp. 131–136
T. Gedeon, L. Koczy: A model of intelligent information retrieval using fuzzy tolerance relations based on hierarchical co-occurrence of words. In: F. Crestani, G. Pasi (ed.), Soft Computing in Information Retrieval: Techniques and Applications, volume50 (Physica Verlag, Heidelberg, 2000 ) pp. 48–74
D.E. Goldberg: Genetic Algorithms in Search, Optimization and Machine Learning ( Addison-Wesley, Reading, MA, 1989 )
R.C. Gonzalez, P. Wintz: Digital Image Processing ( Addison-Wesley, Reading, MA, 1987 )
M.D. Gordon: Probabilistic and genetic algorithms for document retrieval. Communications of the ACM, 31 (10), 208–218 (1988)
J.W. Grzymala-Busse: LERS-A knowledge discovery system. In: L.Polkowski, A.Skowron (eds.), Rough Sets in Knowledge Discovery 2, Applications, Case Studies and Software Systems ( Physica-Verlag, Heidelberg, 1998 ) pp. 562–565
J.W. Grzymala-Busse, W.J. Grzymala-Busse, L.K. Goodwin: A closest fit approach to missing attribute values in preterm birth data. In: Proceedings of RSFDGrC’99 ( Yamaguchi, Japan, November 1999 ) pp. 405–413
A. Gyenesei: A fuzzy approach for mining quantitative association rules. TUCS technical reports 336, University of turku, Department of Computer Science, Lemminkisenkatul4, Finland, March 2000
J. Hale, S. Shenoi: Analyzing FD inference in relational databases. Data and Knowledge Engineering, 18, 167–183 (1996)
X. Hu, N. Cercone: Mining knowledge rules from databases: A rough set approach. In Proceedings of the 12th International Conference on Data Engineering (Washington, February 1996 IEEE Computer Society) pp. 96-105
A. Joshi, R. Krishnapuram: Robust fuzzy clustering methods to support web mining. In: Proc Workshop in Data Mining and Knowledge Discovery, SIGMOD, 1998, 15, pp. 1–8
H. Kargupta: The gene expression messy genetic algorithm. In: Proceedings of the IEEE International Conference on Evolutionary Computation ( Nagoya University, Japan, 1996 ) pp. 631–636
H. Kargupta, B.H. Park, D. Hershberger, E. Johnson: Collective data mining: A new perspective toward distributed data mining. Advances in Distributed and Parallel Knowledge Discovery (MIT/AAAI Press, 1999 )
S. Kawasaki, N.B. Nguyen, T.B. Ho: Hierarchical document clustering based on tolerance rough set model. In: Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining (KDD-2000) Workshop on Text Mining Boston, MA (August 2000)
R. Kewley, M. Embrechta, C. Breneman: Data strip mining for the virtual design of pharmaceuticals with neural networks. IEEE Transactions on Neural Networks, 11, 668–679 (2000)
S. Kim, B.T. Zhang: Web document retrieval by genetic learning of importance factors for html tags. In: Proceedings of the International Workshop on Text and Web mining (Melbourne, Australia, August 2000) pp. 13-23,
A. Koenig: Interactive visualization and analysis of hierarchical neural projections for data mining. IEEE Transactions on Neural Networks, 11, 615–624 (2000)
T. Kohonen: Self-organising Maps (Springer, Berlin, Germany, second edition, 1997 )
T. Kohonen, S. Kaski, K. Lagus, J. Salojarvi, J. Honkela, V. Paatero, A. Saarela: Self organization of a massive document collection. IEEE Transactions on Neural Networks, 11, 574–585 (2000)
D.H. Kraft, F.E. Petry, B.P. Buckles, T. Sadasivan: The use of genetic programming to build queries for information retrieval. In: Proceedings of the IEEE Symposium on Evolutionary Computation ( Orlando, FL, 1994 )
R. Krishnapuram, A. Joshi, L. Yi: A fuzzy relative of the k-medoids algorithm with application to document and snippet clustering. In: Proceedings of IEEE Intl. Conf. Fuzzy Systems–FUZZIEEE 99, Korea, 1999
D.H. Lee, M.H. Kim: Database summarization using fuzzy ISA hierarchies. IEEE Transactions on Systems Man and Cybernetics. Part B-Cybernetics, 27, 68–78 (1997)
R.S.T. Lee, J.N.K. Liu: Tropical cyclone identification and tracking system using integrated neural oscillatory leastic graph matching and hybrid RBF network track mining techniques. IEEE Transactions on Neural Networks, 11, 680–689 (2000)
J.H. Lim: Visual keywords: from text retrieval to multimedia retrieval. In: F.Crestani, G.Pasi (eds.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ), 50, pp. 77–101
R.P. Lippmann: Pattern classification using neural networks. IEEE Communications Magazine, pp. 47–64 (1989)
B. Liu, W. Hsu, L.F. Mun, H.Y. Lee: Finding interesting patterns using user expectation. IEEE Transactions on Knowledge and Data Engineering, 11, 817–832 (1999)
C. Lopes, M. Pacheco, M. Vellasco, E. Passos: Rule-evolver: An evolutionary approach for data mining. In: Proceedings of RSFDGrC’99 ( Yamaguchi, Japan, November 1999 ) pp. 458–462
H.J. Lu, R. Setiono, H. Liu: Effective data mining using neural networks. IEEE Transactions on Knowledge and Data Engineering, 8, 957–961 (1996)
V.U. Maheswari, A. Siromoney, K.M. Mehata: The variable precision rough set model for web usage mining. In: Proceedings of the First Asia-Pacific Con-ference on Web Intelligence (WI-2001) ( Maebashi, Japan, October 2001 )
M.J. Martin-Bautista, M.A. Vila: A survey of genetic feature selection in mining issues. In: Proceedings of the Congress on Evolutionary Computation (CEC 99), 1999 pp. 13–23
L.J. Mazlack: Softly focusing on data. In: Proceedings of NAFIPS 99 ( New York, June 1999 ) pp. 700–704
D. Merkl, A. Rauber: Document classification with unsupervised artificial neural networks. In: F.Crestani, G.Pasi (eds.), Soft Computing in Information Retrieval: Techniques and Applications, volume50, (Physica Verlag, Heidelberg, 2000 ) pp. 102–121
T.M. Mitchell: Machine Learning ( McGraw-Hill, New York, 1997 )
T.M. Mitchell: Machine learning and data mining. Communications of the ACM, 42 (11), 1999
P. Mitra, S. Mitra, S.K. Pal: Staging of cervical cancer with soft computing. IEEE Trans. Biomedical Engineering, 47 (7), 934–940 (2000)
S. Mitra, R.K. De, S.K. Pal: Knowledge-based fuzzy MLP for classification and rule generation. IEEE Transactions on Neural Networks, 8, 1338–1350 (1997)
S. Mitra, Y. Hayashi: Neuro-fuzzy rule generation: Survey in soft computing framework. IEEE Transactions on Neural Networks, 11, 748–768 (2000)
S. Mitra, S.K. Pal: Fuzzy multi-layer perceptron, inferencing and rule gener-ation. IEEE Transactions on Neural Networks, 6, 51–63 (1995)
S. Mitra, S.K. Pal: Fuzzy self organization, inferencing and rule generation. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 26, 608–620, 1996
S. Mitra, S.K. Pal, P. Mitra: Data mining in soft computing framework: A survey. IEEE Trans. Neural Networks, 13 (1), 3–14 (2002)
B. Mobasher, V. Kumar, E.H. Han: Clustering in a high dimensional space using hypergraph models. Technical Report TR-97-063, University of Minnesota, Minneapolis, 1997.
T. Mollestad, A. Skowron: A rough set framework for data mining of propo-sitional default rules. Lecture Notes in Computer Science 1079, 448–457 (1996)
D. Nauck: Using symbolic data in neuro-fuzzy classification. In Proceedings of NAFIPS 99 ( New York, June 1999 ) pp. 536–540
E. Noda, A.A. Freitas, H.S. Lopes: Discovering interesting prediction rules with a genetic algorithm. In: Proceedings of IEEE Congress on Evolutionary Computation CEC 99 ( Washington DC, July 1999 ) pp. 1322–1329
S.K. Pal, R.K. De, J. Basak: Unsupervised feature evaluation: A neuro-fuzzy approach. IEEE Transactions on Neural Networks, 11, 366–376 (2000)
S.K. Pal, T.S. Dillon, D.S. Yeung: Soft Computing in Case Based Reasoning ( Springer Verlag, London, 2001 )
S.K. Pal, D. DuttaMajumder: Fuzzy Mathematical Approach to Pattern Recognition (John Wiley, Halsted Press, New York, 1986 )
S.K. Pal, A. Ghosh, M.K. Kundu (eds.): Soft Computing for Image Processing ( Physica Verlag, Heidelberg, 2000 )
S.K. Pal, P. Mitra: Case generation: A rough fuzzy approach. In: Proc. Intl. Conf. Case Based Reasoning (ICCBR2001) ( Vancouver, Canada, 2001 )
S.K. Pal, S. Mitra: Neuro-fuzzy Pattern Recognition: Methods in Soft Com-puting ( John Wiley, New York, 1999 )
S.K. Pal, S.Mitra, P. Mitra: Rough fuzzy MLP: Modular evolution, rule generation and evaluation. IEEE Trans. Knowledge and Data Engineering, 15 (1), 14–25 (2003)
S.K. Pal, A. Pal (eds.): Pattern Recognition: From classical to modern approaches ( World Scientific, Singapore, 2001 )
S.K. Pal, W. Pedrycz, A. Skowron, R. Swiniarski (eds.): Spl. issue on roughneuro computing. Neurocomputing, 36(1–4) (2001)
S.K. Pal, A. Skowron. Rough Fuzzy Hybridization: A New Trend in Decision Making ( Springer-Verlag, Singapore, 1999 )
S.K. Pal, V. Talwar, P. Mitra: Web mining in soft computing framework: Relevance, state of the art and future direction. IEEE Trans. Neural Networks, 13 (5), 1163–1177 (2002)
S.K. Pal, P.P. Wang (eds.): Genetic Algorithms for Pattern Recognition ( CRC Press, Boca Raton, 1996 )
G. Pasi, G. Bordonga: Application of fuzzy set theory to extend boolean information retrieval. In: F.Crestani, G.Pasi, (eds.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ) 50, pp. 21–47
Z. Pawlak: Rough Sets, Theoretical Aspects of Reasoning about Data ( Kluwer Academic, Dordrecht, 1991 )
M. Pazzani, J. Muramatsu, D. Billsus: Syskill and webert:identifying interesting web sites. In: Proceedings of Thirteenth National Conference on AIpp. 54–61 (1996)
W. Pedrycz: Conditional fuzzy c-means. Pattern Recognition Letters, 17, 625–632 (1996)
W. Pedrycz: Fuzzy set technology in knowledge discovery. Fuzzy Sets and Systems, 98, 279–290 (1998)
L. Polkowski, A. Skowron: Rough mereology: A new paradigm for approximate reasoning. International Journal of Approximate Reasoning, 15(4), 333365 (1996)
L. Polkowski, A. Skowron: Rough Sets in Knowledge Discovery 1 and 2 ( Physica-Verlag, Heidelberg, 1998 )
A. Rosenfeld, A.C. Kak: Digital Picture Processing (Volume 1-2. Academic Press, New York, 1982 )
D.E. Rumelhart, J.L. McClelland (eds.): Parallel Distributed Processing: Explorations in the Microstructures of Cognition, volumel (MIT Press, Cambridge, MA, 1986 )
T. Ryu, C.F. Eick: MASSON: discovering commonalties in collection of objects using genetic programming In: Genetic Programming 1996: Proc. First Annual Conference (Stanford University, CA, July 28-31 1996 MIT Press) pp. 200–208
D. Shalvi, N. De Claris: Unsupervised neural network approach to medical data mining techniques. In: Proceedings of IEEE International Joint Conference on Neural Networks ( Alaska, May 1998 ) pp. 171–176
N. Shan, W. Ziarko: Data-based acquisition and incremental modification of classification rules. Computational Intelligence, 11, 357–370 (1995)
J. Shavlik, T. Eliassi: A system for building intelligent agents that learn to retrieve and extract information. International Journal on User Modeling and user adapted interaction, April 2001 ( Spl. issue on User Modeling and Intelligent Agents )
J. Shavlik, G.G. Towell: Knowledge-based artificial neural networks. Artificial Intelligence, 70 (1-2), 119–165 (1994)
C.K. Shin, S.J. Yu, U.T. Yun, H.K. Kim: A hybrid approach of neural network and memory based learning to data mining. IEEE Transactions on Neural Networks, 11, 637–646 (2000)
A. Skowron: Extracting laws from decision tables–a rough set approach. Computational Intelligence, 11, 371–388 (1995)
A. Skowron, L. Polkowski (eds.), Rough Sets in Knowledge Discovery ( Physica-Verlag, Heidelberg, 1998 )
S. Soderland: Learning information extraction rules for semi-structured and free text. Machine learning, 34 (Special issue on Natural Language Learning) 233–272 (1999)
U. Straccia: A framework for the retrieval of multimedia objects based on four-valued fuzzy description logics. In F.Crestani, G.Pasi, (ed.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ) 50, pp. 332–357
A. Teller, M. Veloso: Program evolution for data mining. The International Journal of Expert Systems, 8, 216–236 (1995)
A.B. Tickle, R. Andrews, M. Golea, J. Diederich: The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks. IEEE Transactions on Neural Networks, 9, 1057–1068 (1998)
J.T. Tou, R.C. Gonzalez: Pattern Recognition Principles ( Addison-Wesley, London, 1974 )
I.B. Turksen: Fuzzy data mining and expert system development. In: Proceedings of IEEE International Conference on Systems, Man, Cybernetics ( San Diego, CA, October 1998 ) pp. 2057–2061
J.Vesanto, E.Alhoniemi: Clustering of the self-organizing map. IEEE Transactions on Neural Networks, 11, 586–600 (2000)
Q.Wei, G.Chen: Mining generalized association rules with fuzzy taxonomic structures. In: Proceedings of NAFIPS 99 ( New York, June 1999 ) pp. 477–481
S.K. Wong, Y.Y. Yao, C.J. Butz: Granular information retrieval. In F.Crestani, G.Pasi (eds.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ) 50, pp. 317–331.
R.Yager: A framework for linguistic and hierarchical queries for document retrieval. In: F.Crestani, G.Pasi (eds.), Soft Computing in Information Retrieval: Techniques and Applications ( Physica Verlag, Heidelberg, 2000 ) 50, pp. 3–20
R.R. Yager: On linguistic summaries of data. In: W.Frawley, G.P. Shapiro (eds.), Knowledge Discovery in Databases ( AAAI/MIT Press, Menlo Park, CA, 1991 ) pp. 347–363
J.J. Yang, R.Korfhage: Query modification using genetic algorithms in vector space models. TR LISO45/I592001, Department of IS, University of Pittsburg (1992)
L.A. Zadeh: Fuzzy sets. Information and Control, 8, 338–353 (1965)
L.A. Zadeh: Fuzzy logic, neural networks, and soft computing. Communications of the ACM, 37, 77–84 (1994)
L.A. Zadeh: A new direction in AI: Towards a computational theory of perceptions. AI Magazine, 22, 73–84 (2001)
W. Ziarko, N. Shan: KDD-R: A comprehensive system for knowledge discovery in databases using rough sets. In: Proc. Third International Workshop on Rough Sets and Soft Computing (RSSC’94, 1994) pp. 164-173
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Pal, S.K., Mitra, S., Mitra, P. (2004). Soft Computing Pattern Recognition, Data Mining and Web Intelligence. In: Intelligent Technologies for Information Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-07952-2_19
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