3. SDM 2003: San Francisco, CA, USA

@proceedings{DBLP:conf/sdm/2003,
  editor    = {Daniel Barbar{\'a} and
               Chandrika Kamath},
  title     = {Proceedings of the Third SIAM International Conference on Data
               Mining, San Francisco, CA, USA, May 1-3, 2003},
  booktitle = {SDM},
  publisher = {SIAM},
  year      = {2003},
  isbn      = {0-89871-545-8},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Part I: Full Papers

• Michael D. Twa, Srinivasan Parthasarathy, Thomas W. Raasch, Mark Bullimore:
  Decision Tree Classification of Spatial Data Patterns from Videokeratography using Zernicke Polynomials.
  
• Ming Jiang, Tat-Sang Choy, Sameep Mehta, Matt Coatney, Steve Barr, Kaden Hazzard, David Richie, Srinivasan Parthasarathy, Raghu Machiraju, David Thompson, John Wilkins, Boyd Gatlin:
  Feature Mining Paradigms for Scientific Data.
  
• Aleksandar Lazarevic, Levent Ertöz, Vipin Kumar, Aysel Ozgur, Jaideep Srivastava:
  A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection.
  
• Matthew Brand:
  Fast Online SVD Revisions for Lightweight Recommender Systems.
  
• Levent Ertöz, Michael Steinbach, Vipin Kumar:
  Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data.
  
• Benjamin C. M. Fung, Ke Wang, Martin Ester:
  Hierarchical Document Clustering using Frequent Itemsets.
  
• Shi Zhong, Joydeep Ghosh:
  Scalable, Balanced Model-based Clustering.
  
• Jonatan Gómez, Dipankar Dasgupta, Olfa Nasraoui:
  A New Gravitational Clustering Algorithm.
  
• Ke Wang, Senqiang Zhou, Ada Wai-Chee Fu, Jeffrey Xu Yu:
  Mining Changes of Classification by Correspondence Tracing.
  
• Dimitris Bertsimas, Adam J. Mersereau, Nitin R. Patel:
  Dynamic Classification of Online Customers.
  
• Ruoming Jin, Gagan Agrawal:
  Communication and Memory Efficient Parallel Decision Tree Construction.
  
• Haixun Wang, Carlo Zaniolo:
  ATLaS: A Native Extension of SQL for Data Mining.
  
• Dmitry Pavlov, Padhraic Smyth:
  Approximate Query Answering by Model Averaging.
  
• Ravi Kothari, Parul A. Mittal, Vivek Jain, Mukesh K. Mohania:
  On using Page Cooccurrences for Computing Clickstream Similarity.
  
• Xifeng Yan, Jiawei Han, Ramin Afshar:
  CloSpan: Mining Closed Sequential Patterns in Large Databases.
  
• Soon Tee Teoh, Kwan-Liu Ma:
  StarClass: Interactive Visual Classification using Star Coordinates.
  
• Dennis DeCoste:
  Anytime Query-Tuned Kernel Machines via Cholesky Factorization.
  
• Douglas R. Hundley, Michael J. Kirby:
  Estimation of Topological Dimension.
  
• Alexander G. Gray, Andrew W. Moore:
  Nonparametric Density Estimation: Toward Computational Tractability.
  
• Ronald K. Pearson:
  Generalized Sensitivity Analysis: A Framework for Evaluating Data Analysis Results.
  
• Jiong Yang, Wei Wang, Philip S. Yu:
  STAMP: On Discovery of Statistically Important Pattern Repeats in Long Sequential Data.
  

Part II: Poster Presentations

• Hiroshi Mamitsuka:
  Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data.
  
• Huan Li, Hongjun Lu, Lei Yu:
  Active Sampling: An Effective Approach to Feature Selection.
  
• Chris H. Q. Ding, Xiaofeng He, Parry Husbands, Hongyuan Zha, Horst D. Simon:
  PageRank: HITS and a Unified Framework for Link Analysis.
  
• Patricia B. Cerrito, James Cox:
  The Application of Text Mining Software to Examine Coded Information.
  
• Tassos Argyros, Charis Ermopoulos, Vassiliki Pavlaki, Nidal Al-Said:
  Extracting Cyber Communities through Patterns.
  
• Bi-Ru Dai, Cheng-Ru Lin, Ming-Syan Chen:
  On the Techniques for Data Clustering with Numerical Constraints.
  
• Patricia B. Cerrito, George R. Barnes, Robert W. Forbes:
  The Analysis of Asthma and Exposure Data using Geographic Information Systems and Data Mining Information.
  
• Ronald K. Pearson, Harri Lähdesmäki, Heikki Huttunen, Olli Yli-Harja:
  Detecting Periodicity in Nonideal Datasets.
  
• Slobodan Vucetic, Dragoljub Pokrajac, Hongbo Xie, Zoran Obradovic:
  Detection of Underrepresented Biological Sequences using Class-Conditional Distribution Models.
  
• R. Chen, Krishnamoorthy Sivakumar, H. Khargupta:
  Learning Bayesian Network Structure from Distributed Data.
  
• Jaakko Hollmén, Jouni K. Seppänen, Heikki Mannila:
  Mixture Models and Frequent Sets: Combining Global and Local Methods for 0-1 Data.
  
• Dennis Lucarelli, Cheryl Resch, I-Jeng Wang, Fernando J. Pineda:
  Field-Theoretic Methods for Intractable Probabilistic Models.
  
• Sergio M. Savaresi, Simone Garatti, Sergio Bittanti, Luca La Brocca:
  Data-Mining of a Large Virtual Community: Relationship between Users DB and the Web-Log File.
  
• Alain Casali, Rosine Cicchetti, Lotfi Lakhal:
  Cube Lattices: A Framework for Multidimensional Data Mining.
  

Part III: Student Papers

• Hye-Chung Kum, Jian Pei, Wei Wang, Dean Duncan:
  ApproxMAP: Approximate Mining of Consensus Sequential Patterns.
  
• Hunor Albert-Lorincz, Jean-François Boulicaut:
  Mining Frequent Sequential Patterns under Regular Expressions: A Highly Adaptive Strategy for Pushing Contraints.
  
• Yan Liu, John R. Kender:
  Sort-Merge Feature Selection for Video Data.
  
• Song Lin, Donald E. Brown:
  An Outlier-based Data Association Method for Linking Criminal Incidents.
  
• Xiaoxin Yin, Jiawei Han:
  CPAR: Classification based on Predictive Association Rules.
  
• Wen Niu, Raj Bhatnagar:
  Mining Temporal Databases for Subsequence Patterns.
  
• David Littau, Daniel Boley:
  Using Low-Memory Representations to Cluster Very Large Data Sets.