5. SDM 2005: Newport Beach, California, USA

Statistics in Data Mining

• Sijin Liu, Xiaotong Shen, Wing Hung Wong: Computational Developments of Psi-learning.
• Matthew Brand: A Random Walks Perspective on Maximizing Satisfaction and Profit.
• Ronald K. Pearson: Surveying Data for Patchy Structure.
• Chris H. Q. Ding, Jieping Ye: 2-Dimensional Singular Value Decomposition for 2D Maps and Images.

Stream Data Mining

• Graham Cormode, S. Muthukrishnan: Summarizing and Mining Skewed Data Streams.
• Charu C. Aggarwal, Philip S. Yu: Online Analysis of Community Evolution in Data Streams.
• Chih-Hsiang Lin, Ding-Ying Chiu, Yi-Hung Wu, Arbee L. P. Chen: Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window.
• Charu C. Aggarwal: On Abnormality Detection in Spuriously Populated Data Streams.

Privacy Preserving Data Mining

• Zhiqiang Yang, Sheng Zhong, Rebecca N. Wright: Privacy-Preserving Classification of Customer Data without Loss of Accuracy.
• Xintao Wu, Ying Wu, Yongge Wang, Yingjiu Li: Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining.
• Charu C. Aggarwal, Philip S. Yu: On Variable Constraints in Privacy Preserving Data Mining.

Clustering

• David Gondek, Shivakumar Vaithyanathan, Ashutosh Garg: Clustering with Model-level Constraints.
• Ian Davidson, S. S. Ravi: Clustering with Constraints: Feasibility Issues and the k-Means Algorithm.
• Yu Xia, Jiming Peng: A Cutting Algorithm for the Minimum Sum-of-Squared Error Clustering.

Scientific Data Mining

• Sameep Mehta, Steve Barr, Tat-Sang Choy, Hui Yang, Srinivasan Parthasarathy, Raghu Machiraju, John Wilkins: Dynamic Classification of Defect Structures in Molecular Dynamics Simulation Data.
• Bavani Arunasalam, Sanjay Chawla, Pei Sun: Striking Two Birds With One Stone: Simultaneous Mining of Positive and Negative Spatial Patterns.
• Ata Kabán, Louisa Nolan, Somak Raychaudhury: Finding Young Stellar Populations in Elliptical Galaxies from Independent Components of Optical Spectra.

Classifiers and Ensembles

• Qinghua Hu: Hybrid Data Reduction with Fuzzy Rough Set Theory for Classification.
• Jianyong Wang, George Karypis: HARMONY: Efficiently Mining the Best Rules for Classification.
• Carlotta Domeniconi, Bojun Yan: On Error Correlation and Accuracy of Nearest Neighbor Ensemble Classifiers.

Association Rules and Database Issues

• Yiqiu Han, Wai Lam: Lazy Learning for Classification Based on Query Projections.
• Bart Goethals, Juho Muhonen, Hannu Toivonen: Mining Non-Derivable Association Rules.
• Toon Calders, Bart Goethals: Depth-First Non-Derivable Itemset Mining.
• Dmitri V. Kalashnikov, Sharad Mehrotra, Zhaoqi Chen: Exploiting Relationships for Domain-Independent Data Cleaning.

Graphs and Graphical Models

• Scott White, Padhraic Smyth: A Spectral Clustering Approach To Finding Communities in Graph.
• Chao Liu, Xifeng Yan, Hwanjo Yu, Jiawei Han, Philip S. Yu: Mining Behavior Graphs for "Backtrace" of Noncrashing Bugs.
• Tak-Lam Wong, Wai Lam: Learning to Refine Ontology for a New Web Site Using a Bayesian Approach.
• Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao: Exploiting Parameter Related Domain Knowledge for Learning in Graphical Models.

SVM and Classification

• Navneet Panda, Edward Y. Chang: Exploiting Geometry for Support Vector Machine Indexing.
• Shibin Qiu, Terran Lane: Parallel Computation of RBF Kernels for Support Vector Classifiers.
• Yun Chi, Philip S. Yu, Haixun Wang, Richard R. Muntz: Loadstar: A Load Shedding Scheme for Classifying Data Streams.

Complex Data Types: Text, Images, and Sequences

• Ying Zhao, George Karypis: Topic-driven Clustering for Document Datasets.
• Tomás Singliar, Milos Hauskrecht: Variational Learning for Noisy-OR Component Analysis.
• Gemma Casas-Garriga: Summarizing Sequential Data with Closed Partial Orders.

Statistics in Data Mining

• Kwok Pan Pang: SUMSRM: A New Statistic for the Structural Break Detection in Time Series.
• Robert Gwadera, Mikhail J. Atallah, Wojciech Szpankowski: Markov Models for Identification of Significant Episodes.
• Congnan Luo, Soon Myoung Chung: Efficient Mining of Maximal Sequential Patterns Using Multiple Samples.

Scientific Data Mining

• Naren Ramakrishnan, Chris Bailey-Kellogg, Satish Tadepalli, Varun Pandey: Gaussian Processes for Active Data Mining of Spatial Aggregates.
• Xiaoli Zhang Fern, Carla E. Brodley, Mark A. Friedl: Correlation Clustering for Learning Mixtures of Canonical Correlation Models.
• Michail Vlachos, Philip S. Yu, Vittorio Castelli: On Periodicity Detection and Structural Periodic Similarity.

Poster Papers

• Jian Pei, Moonjung Cho, David Wai-Lok Cheung: Cross Table Cubing: Mining Iceberg Cubes from Data Warehouses.
• Amir Bar-Or, Ran Wolff, Assaf Schuster, Daniel Keren: Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases.
• Daniel Lemire, Anna Maclachlan: Slope One Predictors for Online Rating-Based Collaborative Filtering.
• Murat Dundar, Glenn Fung, Jinbo Bi, Sathyakama Sandilya, R. Bharat Rao: Sparse Fisher Discriminant Analysis for Computer Aided Detection.
• Hamad Alhammady, Kotagiri Ramamohanarao: Expanding the Training Data Space Using Emerging Patterns and Genetic Methods.
• Wei Fan, Janek Mathuria, Chang-Tien Lu: Making Data Mining Models Useful to Model Non-paying Customers of Exchange Carriers.
• Shuting Xu, Jun Zhang: Matrix Condition Number Prediction with SVM Regression and Feature Selection.
• Reda Alhajj: Cluster Validity Analysis of Alternative Results from Multi-Objective Optimization.
• Kuo-Yu Huang, Chia-Hui Chang, Kuo-Zui Lin: ClosedPROWL: Efficient Mining of Closed Frequent Continuities by Projected Window List Technology.
• Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh: Three Myths about Dynamic Time Warping Data Mining.
• Effrosini Kokiopoulou, Yousef Saad: PCA and kernel PCA using polynomial filtering: a case study on face recognition.
• Raymond Chi-Wing Wong, Ada Wai-Chee Fu: Mining Top-K Itemsets over a Sliding Window Based on Zipfian Distribution.
• Tao Li: Hierarchical Document Classification Using Automatically Generated Hierarchy.
• Tao Li: On Clustering Binary Data.
• Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) Ratanamahatana: Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases.
• Rong She, Ke Wang, Yabo Xu, Philip S. Yu: Pushing Feature Selection Ahead Of Join.
• Shiying Huang, Geoffrey I. Webb: Discarding Insignificant Rules during Impact Rule Discovery in Large, Dense Databases.
• Himika Biswas, Somnath Pal: SPID4.7: Discretization Using Successive Pseudo Deletion at Maximum Information Gain Boundary Points.
• Zheng Sun, Philip S. Yu, Xiang-Yang Li: Iterative Mining for Rules with Constrained Antecedents.
• Al Mamunur Rashid, George Karypis, John Riedl: Influence in Ratings-Based Recommender Systems: An Algorithm-Independent Approach.
• Gianluigi Greco, Antonella Guzzo, Giuseppe Manco, Domenico Saccà: Mining Unconnected Patterns in Workflows.
• Bharath Kumar Mohan: The Best Nurturers in Computer Science Research.
• Tsuyoshi Idé, Keisuke Inoue: Knowledge Discovery from Heterogeneous Dynamic Systems using Change-Point Correlations.
• Ke Wang, Yabo Xu, Philip S. Yu, Rong She: Building Decision Trees on Records Linked through Key References.
• Giuliano Tirenni, Abderrahim Labbi, André Elisseeff, Cesar Berrospi: Efficient Allocation of Marketing Resources using Dynamic Programming.
• Haixun Wang, Chang-Shing Perng, Philip S. Yu: Near-Neighbor Search in Pattern Distance Spaces.
• Haiyun Bian, Raj Bhatnagar: An Algorithm for Well Structured Subspace Clusters.
• Vincent Shin-Mu Tseng, Chao-Hui Lee: CBS: A New Classification Method by Using Sequential Patterns.
• Hong Cheng, Xifeng Yan, Jiawei Han: SeqIndex: Indexing Sequences by Sequential Pattern Analysis.
• Chris H. Q. Ding, Xiaofeng He: On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering.
• Gang Wu, Zhihua Zhang, Edward Y. Chang: Kronecker Factorization for Speeding up Kernel Machines.
• Feng Kang, Rong Jin: Symmetric Statistical Translation Models for Automatic Image Annotation.
• Kang Peng, Slobodan Vucetic, Zoran Obradovic: Correcting Sampling Bias in Structural Genomics through Iterative Selection of Underrepresented Targets.
• Alina Beygelzimer, Emre Erdogan, Sheng Ma, Irina Rish: Statictical Models for Unequally Spaced Time Series.
• Efstratios Gallopoulos, Dimitrios Zeimpekis: CLSI: A Flexible Approximation Scheme from Clustered Term-Document Matrices.
• Unil Yun, John J. Leggett: WFIM: Weighted Frequent Itemset Mining with a weight range and a minimum weight.
• Martin H. C. Law, Alexander P. Topchy, Anil K. Jain: Model-based Clustering With Probabilistic Constraints.

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