Table of Contents

• Metric sensitivity of reciprocal relationship bonds in the knowledge discovery processBelur V. Dasarathy. 2-10 [doi]
• Discovering fuzzy clusters in databases using an evolutionary approachLewis L. H. Chung, Keith C. C. Chan, Henry Leung. 11-21 [doi]
• Distance functions in dynamic integration of data mining techniquesSeppo Puuronen, Alexey Tsymbal, Vagan Y. Terziyan. 22-32 [doi]
• Value-based customer grouping from large retail data setsAlexander Strehl, Joydeep Ghosh. 33-42 [doi]
• Classification analysis of customer satisfaction and repeat buyers survey dataGirish Kulkarni. 43-48 [doi]
• Design of a hybrid model classifier for data mining applicationsSayee Sumathi, S. N. Sivanandam, R. Ravindran. 49-61 [doi]
• Genetic-algorithm-based optimization of a fuzzy logic resource manager for electronic attackJames F. Smith III, Robert D. Rhyne II. 62-73 [doi]
• Discovery of approximate concepts in clinical databases based on a rough set modelShusaku Tsumoto. 74-81 [doi]
• Granularity refined by knowledge: contingency tables and rough sets as tools of discoveryJan M. Zytkow. 82-91 [doi]
• Numerical-linguistic knowledge discovery using granular neural networksYanqing Zhang. 92-99 [doi]
• Fuzzification of attribute-oriented generalization and its application to medicineShusaku Tsumoto. 100-107 [doi]
• Information tables with neighborhood semanticsYiyu Yao. 108-116 [doi]
• Knowledge acquisition: neural network learningGuoyin Wang, Paul S. Fisher. 117-129 [doi]
• Auditing health insurance reimbursement by constructing association rulesI-Jen Chiang. 130-137 [doi]
• Discovering spatial associations in imagesOsmar R. Zaïane, Jiawei Han. 138-147 [doi]
• Data mining approach using machine-oriented modeling: finding association rules using canonical namesEric Louie, Tsau Y. Lin. 148-154 [doi]
• Using closed itemsets in association rule mining with taxonomiesPetteri Sevon. 155-162 [doi]
• Distributed data mining: an attribute-oriented key-preserving methodMaybin K. Muyeba, John A. Keane. 163-172 [doi]
• Customer and household matching: resolving entity identity in data warehousesDonald J. Berndt, Ronald K. Satterfield. 173-180 [doi]
• Rule generation based on rough set theoryGuoyin Wang, Yu Wu, Paul S. Fisher. 181-191 [doi]
• Theoretical sampling for data miningTsau Y. Lin. 192-200 [doi]
• Trend similarity and prediction in time-series databasesJong P. Yoon, Jieun Lee, Sungrim Kim. 201-212 [doi]
• Mining sequential patterns including time intervalsMariko Yoshida, Tetsuya Iizuka, Hisako Shiohara, Masanori Ishiguro. 213-220 [doi]
• How can knowledge discovery methods uncover spatio-temporal patterns in environmental data?Monica Wachowicz. 221-229 [doi]
• Cycle mining in active database environmentsJennifer Seitzer, James P. Buckley. 230-239 [doi]
• Autonomous visual discoveryMichael C. Burl, Dominic Lucchetti. 240-249 [doi]
• Knowledge discovery in scientific dataStephan Rudolph. 250-258 [doi]
• Challenges and solutions to mining Earth science dataRahul Ramachandran, Helen Conover, Sara J. Graves, Ken Keiser. 259-264 [doi]
• Mining remote sensing image data: an integration of fuzzy set theory and image understanding techniques for environmental change detectionPeter W. Eklund, Jane You, Peter J. Deer. 265-272 [doi]
• Systematic method to identify patterns in engineering dataPeter Hertkorn, Stephan Rudolph. 273-280 [doi]
• Integration inconsistency removal in data miningJulius Stuller. 281-291 [doi]
• NASA aviation safety program: Aircraft Engine Health Management Data Mining Tools roadmapJonathan S. Litt, Donald L. Simon, Claudia Meyer, Hans DePold, J. R. Curtis, Howard Winston, Yao Wang, Irving C. Statler, Yuri Gawdiak. 292-298 [doi]
• Toward text understanding: classification of text documents by word mapAri Visa, Jarmo Toivanen, Barbro Back, Hannu Vanharanta. 299-307 [doi]
• Application of syntactic methods of pattern recognition for data mining and knowledge discovery in medicineMarek R. Ogiela, Ryszard Tadeusiewicz. 308-318 [doi]
• Correlation of HIV protease structure with Indinavir resistance: a data mining and neural networks approachSorin Draghici, Lonnie T. Cumberland Jr., Ladislau C. Kovari. 319-329 [doi]
• Data mining algorithm for discovering matrix association regions (MARs)Gautam B. Singh, Stephen A. Krawetz. 330-341 [doi]
• Data mining approaches for information retrieval from genomic databasesDonglin Liu, Gautam B. Singh. 342-351 [doi]
• Application of hidden Markov models to biological data mining: a case studyMichael M. Yin, Jason T. L. Wang. 352-358 [doi]
• Mining knowledge in medical image databasesPetra Perner. 359-368 [doi]
• Data mining and intelligent queries in a knowledge-based multimedia medical database systemShuhua Zhang, John D. Coleman. 369-379 [doi]
• Adapting the right web pages to the right usersHui Xiong, Sam Yuan Sung, Stephen Huang. 380-387 [doi]
• Data mining for the e-business: developments and directionsAlfred Grasso, Harry Sleeper, Bhavani M. Thuraisingham, Yike Guo. 388-392 [doi]
• Harnessing agent technologies for data mining and knowledge discoveryJenifer S. McCormack, Brian Wohlschlaeger. 393-400 [doi]
• Application of data mining and knowledge discovery in emergency models and simulationsEduardo R. Sevilla. 401-408 [doi]
• National traffic system evaluation using data mining techniquesEdmond C. P. Chang. 409-411 [doi]
• Using KDD to analyze the impact of curriculum revisions in a Brazilian universityKarin Becker, Cinara Guellner Ghedini, Egidio L. Terra. 412-419 [doi]
• Self-organized neural network scheme as a data mining toolSayee Sumathi, S. N. Sivanandam, Jagadeeswari. 420 [doi]