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ORCID2nd KDD 1996: Portland, Oregon, USA
- Evangelos Simoudis, Jiawei Han, Usama M. Fayyad:
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland, Oregon, USA. AAAI Press 1996, ISBN 1-57735-004-9
Regular Papers
Combining Data Mining and Machine Learning
- Philip K. Chan, Salvatore J. Stolfo:
Sharing Learned Models among Remote Database Partitions by Local Meta-Learning. 2-7 - Tom Fawcett, Foster J. Provost:
Combining Data Mining and Machine Learning for Effective User Profiling. 8-13 - Truxton Fulton, Simon Kasif, Steven Salzberg, David L. Waltz:
Local Induction of Decision Trees: Towards Interactive Data Mining. 14-19 - Ivo L. Hofacker, Martijn A. Huynen, Peter F. Stadler, Paul E. Stolorz:
Knowledge Discovery in RNA Sequence Families of HIV Using Scalable Computers. 20-25 - David W. Pfitzner, John K. Salmon:
Parallel Halo Finding in N-Body Cosmology Simulations. 26-31 - Eddie C. Shek, Richard R. Muntz, Edmond Mesrobian, Kenneth W. Ng:
Scalable Exploratory Data Mining of Distributed Geoscientific Data. 32-37
Data Mining Applications
- Victor Ciesielski, Gregory Palstra:
Using a Hybrid Neural/Expert System for Data Base Mining in Market Survey Data. 38-43 - Beatriz de la Iglesia, Justin C. W. Debuse, Victor J. Rayward-Smith:
Discovering Knowledge in Commercial Databases Using Modern Heuristic Techniques. 44-49 - Usama M. Fayyad, David Haussler, Paul E. Stolorz:
KDD for Science Data Analysis: Issues and Examples. 50-56 - Gregory M. Provan, Moninder Singh:
Data Mining and Model Simplicity: A Case Study in Diagnosis. 57-62 - Shusaku Tsumoto, Hiroshi Tanaka:
Automated Discovery of Medical Expert System Rules from Clinical Databases Based on Rough Sets. 63-69 - Jason Tsong-Li Wang, Bruce A. Shapiro, Dennis E. Shasha, Kaizhong Zhang, Chia-Yo Chang:
Automated Discovery of Active Motifs in Multiple RNA Secondary Structures. 70-75 - Rüdiger Wirth, Thomas P. Reinartz:
Detecting Early Indicator Cars in an Automotive Database: A Multi-Strategy Approach. 76-81
Data Mining and Its Applications: A General Overview
- Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth:
Knowledge Discovery and Data Mining: Towards a Unifying Framework. 82-88 - Gregory Piatetsky-Shapiro, Ronald J. Brachman, Tom Khabaza, Willi Klösgen, Evangelos Simoudis:
An Overview of Issues in Developing Industrial Data Mining and Knowledge Discovery Applications. 89-95
Decision-Tree and Rule Induction
- Pedro M. Domingos:
Linear-Time Rule Induction. 96-101 - A. J. Feelders:
Learning from Biased Data Using Mixture Models. 102-107 - Andreas Ittner, Michael Schlosser:
Discovery of Relevant New Features by Generating Non-Linear Decision Trees. 108-113 - Ron Kohavi, Mehran Sahami:
Error-Based and Entropy-Based Discretization of Continuous Features. 114-119
Learning, Probability, and Graphical Models
- Ron Musick:
Rethinking the Learning of Belief Network Probabilities. 120-125 - Padhraic Smyth:
Clustering Using Monte Carlo Cross-Validation. 126-133 - Paul E. Stolorz, Philip C. Chew:
Harnessing Graphical Structure in Markov Chain Monte Carlo Learning. 134-139
Mining with Noise and Missing Data
- Kamakshi Lakshminarayan, Steven A. Harp, Robert P. Goldman, Tariq Samad:
Imputation of Missing Data Using Machine Learning Techniques. 140-145 - Heikki Mannila, Hannu Toivonen:
Discovering Generalized Episodes Using Minimal Occurrences. 146-151
Pattern-Oriented Data Mining
- Wei-Min Shen, Bing Leng:
Metapattern Generation for Integrated Data Mining. 152-157 - Jan M. Zytkow, Robert Zembowicz:
Automated Pattern Mining with a Scale Dimension. 158-163
Prediction and Deviation
- Andreas Arning, Rakesh Agrawal, Prabhakar Raghavan:
A Linear Method for Deviation Detection in Large Databases. 164-169 - Robert Engels:
Planning Tasks for Knowledge Discovery in Databases; Performing Task-Oriented User-Guidance. 170-175 - Petri Kontkanen, Petri Myllymäki, Henry Tirri:
Predictive Data Mining with Finite Mixtures. 176-182 - Rense Lange:
An Empirical Test of the Weighted Effect Approach to Generalized Prediction Using Recursive Neural Nets. 183-188 - Heikki Mannila, Hannu Toivonen:
Multiple Uses of Frequent Sets and Condensed Representations (Extended Abstract). 189-194 - Brij M. Masand, Gregory Piatetsky-Shapiro:
A Comparison of Approaches for Maximizing Business Payoff of Prediction Models. 195-201
Scalability and Extensibility of Data Mining Systems
- Ron Kohavi:
Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. 202-207 - Paul E. Stolorz, Christopher Dean:
Quakefinder: A Scalable Data Mining System for Detecting Earthquakes from Space. 208-213 - Stefan Wrobel, Dietrich Wettschereck, Edgar Sommer, Werner Emde:
Extensibility in Data Mining Systems. 214-219
Spatial, Text and Multimedia Data Mining
- Andrzej Czyzewski:
Mining Knowledge in Noisy Audio Data. 220-225 - Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu:
A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. 226-231 - Kenneth A. Kaufman, Ryszard S. Michalski:
A Method for Reasoning with Structured and Continuous Attributes in the INLEN-2 Multistrategy Knowledge Discovery System. 232-237 - Krista Lagus, Timo Honkela, Samuel Kaski, Teuvo Kohonen:
Self-Organizing Maps of Document Collections: A New Approach to Interactive Exploration. 238-243
Systems for Mining Large Databases
- Rakesh Agrawal, Manish Mehta, John C. Shafer, Ramakrishnan Srikant, Andreas Arning, Toni Bollinger:
The Quest Data Mining System. 244-249 - Jiawei Han, Yongjian Fu, Wei Wang, Jenny Chiang, Wan Gong, Krzysztof Koperski, Deyi Li, Yijun Lu, Amynmohamed Rajan, Nebojsa Stefanovic, Betty Xia, Osmar R. Zaïane:
DBMiner: A System for Mining Knowledge in Large Relational Databases. 250-255 - Tomasz Imielinski, Aashu Virmani, Amin Abdulghani:
DataMine: Application Programming Interface and Query Language for Database Mining. 256-262
KDD-96 Technology Spotlight: Concise Papers
Application of Mathematical Theories
- Micheline Kamber, Rajjan Shinghal:
Evaluating the Interestingness of Characteristic Rules. 263-266 - Alvaro E. Monge, Charles Elkan:
The Field Matching Problem: Algorithms and Applications. 267-270 - Ning Shan, Wojciech Ziarko, Howard J. Hamilton, Nick Cercone:
Discovering Classification Knowledge in Databases Using Rough Sets. 271-274 - Einoshin Suzuki, Masamichi Shimura:
Exceptional Knowledge Discovery in Databases Based on Information Theory. 275-278 - Takao Terano, Yoko Ishino:
Interactive Knowledge Discovery from Marketing Questionnaire Using Simulated Breeding and Inductive Learning Methods. 279-282 - Yang Wang, Andrew K. C. Wong:
Representing Discovered Patterns Using Attributed Hypergraph. 283-286
Data Mining: Integration and Application
- Rakesh Agrawal, Kyuseok Shim:
Developing Tightly-Coupled Data Mining Applications on a Relational Database System. 287-290 - M. Ganesh, Jaideep Srivastava, Travis Richardson:
Mining Entity-Identification Rules for Database Integration. 291-294 - Don R. Swanson, Neil R. Smalheiser:
Undiscovered Public Knowledge: A Ten-Year Update. 295-298
Genetic Algorithms
- Ian W. Flockhart, Nicholas J. Radcliffe:
A Genetic Algorithm-Based Approach to Data Mining. 299-302 - Tae-Wan Ryu, Christoph F. Eick:
Deriving Queries from Results Using Genetic Programming. 303-306
Mining Association Rules
- David Wai-Lok Cheung, Vincent T. Y. Ng, Benjamin W. Tam:
Maintenance of Discovered Knowledge: A Case in Multi-Level Association Rules. 307-310 - Arno J. Knobbe, Pieter W. Adriaans:
Analysing Binary Associations. 311-314
Rule Induction and Decision Tree Induction
- Kevin J. Cherkauer, Jude W. Shavlik:
Growing Simpler Decision Trees to Facilitate Knowledge Discovery. 315-318 - Pedro M. Domingos:
Efficient Specific-to-General Rule Induction. 319-322 - Robert L. Grossman, Haim Bodek, Dave Northcutt, H. Vincent Poor:
Data Mining and Tree-Based Optimization. 323-326 - Pat Langley:
Induction of Condensed Determinations. 327-330 - Ron Rymon:
SE-Trees Outperform Decision Trees in Noisy Domains. 331-334 - Mehran Sahami:
Learning Limited Dependence Bayesian Classifiers. 335-338 - David Urpani, Xindong Wu, Jim Sykes:
RITIO - Rule Induction Two In One. 339-342
Spatial, Temporal, and Multimedia Data Mining
- Ronen Feldman, Haym Hirsh:
Mining Associations in Text in the Presence of Background Knowledge. 343-346 - Edwin M. Knorr, Raymond T. Ng:
Extraction of Spatial Proximity Patterns by Concept Generalization. 347-350 - Balaji Padmanabhan, Alexander Tuzhilin:
Pattern Discovery in Temporal Databases: A Temporal Logic Approach. 351-354
Special Data Mining Techniques
- John M. Aronis, Foster J. Provost, Bruce G. Buchanan:
Exploiting Background Knowledge in Automated Discovery. 355-358 - Gerald Fahner:
Data Mining with Sparse and Simplified Interaction Selection. 359-362 - Thomas Hofmann, Joachim M. Buhmann:
Inferring Hierarchical Clustering Structures by Deterministic Annealing. 363-366 - George H. John, Pat Langley:
Static Versus Dynamic Sampling for Data Mining. 367-370 - Stefan Kramer, Bernhard Pfahringer:
Efficient Search for Strong Partial Determinations. 371-374 - Stephen McKearney, Huw Roberts:
Reverse Engineering Databases for Knowledge Discovery. 375-378 - Marco Richeldi, Pier Luca Lanzi:
Performing Effective Feature Selection by Investigating the Deep Structure of the Data. 379-383
Invited Papers
- Georges G. Grinstein:
Harnessing the Human in Knowledge Discovery. 384-385 - Jeffrey D. Ullman:
Efficient Implementation of Data Cubes Via Materialized Views. 386-388
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