2. KDD 1996:
Portland, Oregon, USA
Evangelos Simoudis, Jiawei Han, Usama M. Fayyad (Eds.):
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 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
Decision-Tree and Rule Induction
Learning, Probability, and Graphical Models
Mining with Noise and Missing Data
Pattern-Oriented Data Mining
Prediction and Deviation
Scalability and Extensibility of Data Mining Systems
Spatial, Text and Multimedia Data Mining
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
Data Mining:
Integration and Application
Genetic Algorithms
Mining Association Rules
Rule Induction and Decision Tree Induction
Spatial, Temporal, and Multimedia Data Mining
Special Data Mining Techniques
Invited Papers
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