KDD2010 features high quality peer-reviewed papers on all aspects of data mining. The accepted papers are below.

• Research Full Presentations
• Research Short Presentations
• Industrial Full Presentations
• Industrial Short Presentations

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A Hierarchical Information Theoretic Technique for the Discovery of Non Linear Alternative Clusterings
Xuan Hong Dang, The University of Melbourne; James Bailey, The University of Melbourne

A Scalable Two-Stage Approach for a Class of Dimensionality Reduction Techniques
Liang Sun, Arizona State University; Betul Ceran, Arizona State University; Jieping Ye, Arizona State University

A Statistical Model for Popular Event Tracking in Social Communities
Xide Lin, Univ. of Illinois,Urbana Champaign; Bo Zhao, Univ. of Illinois,Urbana Champaign; Qiaozhu Mei, Univ. of Michigan; Jiawei Han, Univ. of Illinois,Urbana Champaign

An Efficient Algorithm for a Class of Fused Lasso Problems
Jun Liu, Arizona State University; Lei Yuan, Arizona State University; Jieping Ye, Arizona State University

An efficient causal discovery algorithm for linear models
Zhenxing Wang, The Chinese University of Hong Kong; Laiwan Chan, The Chinese University of Hong Kong

An Energy-Efficient Mobile Recommender System
Yong Ge, Rutgers University; Hui Xiong, Rutgers University; Alexander Tuzhilin, Stern School of Business, New York University; Keli Xiao, Rutgers University; Marco Gruteser, Rutgers University

Balanced Allocation with Succinct Representation
Saeed Alaei, University of Maryland; Ravi Kumar, Yahoo; Azaraksh Malekian, University of Maryland; Erik Vee, Yahoo! Research

Class-Specific Error Bounds for Ensemble Classifiers
Ryan Prenger, Lawrence Livermore National Laboratory; Tracy Lemmond, Lawrence Livermore National Laboratory; Barry Chen, Lawrence Livermore National Laboratory; Kush Varshney, Massachusetts Institute of Technology; William Hanley, Lawrence Livermore National Laboratory

Clustering by Synchronization
Christian Böhm, University of Munich; Claudia Plant, Technische Universität München; Junming Shao, University of Munich; Qinli Yang, University of Edinburgh

Collusion-Resistant Privacy-Preserving Data Mining
Bin Yang, The University of Tokyo; Hiroshi Nakagawa, The University of Tokyo; issei Sato, The University of Tokyo; Jun Sakuma, University of Tsukuba

Combined Regression and Ranking
D. Sculley, Google, Inc

Combining Predictions for Accurate Recommender Systems
Michael Jahrer, Commendo research & consulting; Andreas Töscher, Commendo research & consulting; Robert Legenstein, Graz University of Technology

Community Outliers and their Efficient Detection in Information Networks
Jing Gao, Univ. of Illinois,Urbana Champaign; Feng Liang, Univ. of Illinois,Urbana Champaign; Wei Fan, IBM T.J.Watson; Chi Wang, UIUC; Yizhou Sun,Univ. of Illinois,Urbana Champaign; Jiawei Han, Univ. of Illinois,Urbana Champaign

Compressed Fisher Linear Discriminant Analysis: Classification of Randomly Projected Data
Robert Durrant, University of Birmingham; Ata Kaban, University of Birmingham

Connecting the Dots Between News Articles
Dafna Shahaf, Carnegie Mellon Univ.; Carlos Guestrin, Carnegie Mellon Univ.

Data Mining with Differential Privacy
Arik Friedman, Technion; Assaf Schuster, Technion

Designing efficient cascaded classifiers: Tradeoff between accuracy and cost
Vikas Raykar, Siemens Healthcare; Balaji Krishnapuram, Siemens Healthcare; Shipeng Yu, Siemens Healthcare

Discovering frequent patterns in sensitive data
Raghav Bhaskar, Microsoft Research; Srivatsan Laxman, Microsoft Research; Adam Smith, Pennsylvania State University; Abhradeep Thakurta, Pennsylvania State University

Discovering Significant Relaxed Order-Preserving Submatrices
Qiong FANG, Hong Kong UST; Wilfred Ng, Hong Kong UST; Jianlin Feng, Sun Yat-sen University

Discriminative Topic Modeling based on Manifold Learning
Seungil Huh, Carnegie Mellon University; Stephen Fienberg, Carnegie Mellon University

Document Clustering via Dirichlet Process Mixture Model with Feature Selection
Guan Yu, ; Ruizhang Huang, The Hong Kong Polytechnic Univ; Zhaojun Wang,

DUST: A Generalized Notion of Similarity between Uncertain Time Series
Smruti Sarangi, IBM Research - India; Karin Murthy, IBM Research - India

Estimating Rates of Rare Events with Multiple Hierarchies through Scalable Log-linear Models
Deepak Agarwal, Rahul Agrawal; Nagaraj Kota, ; Rahul Agrawal, ; Rajiv Khanna,

Evolutionary Hierarchical Dirichlet Processes for Multiple Correlated Time-varying Corpora
Jianwen Zhang, Tsinghua University; Yangqiu Song, IBM China; Changshui Zhang, Tsinghua University; Shixia Liu, IBM China

Extracting Temporal Signatures for Comprehending Systems Biology Models
Naren Sundaravaradan, Virginia Tech; K. S. M. Tozammel Hossain, Virginia Tech; Vandana Sreedharan, Virginia Tech; John Paul Vergara, Ateneo de Manila University; Lenwood Heath, Virginia Tech; Douglas Slotta, NIH/NCBI; Naren Ramakrishnan, Virginia Tech

Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis, Applications
William March, Georgia Institute of Technolog; Parikshit Ram, Georgia Institute of Technology; Alexander Gray, Georgia Institute of Technology

Fast Nearest Neighbor Search in Disk-resident Graphs
Purnamrita Sarkar, Cargnegie Mellon Univ.; Andrew Moore, Google Inc.

Fast Online Learning through Effective Offline Initialization for Time-Sensitive Recommendation
Bee-Chung Chen, Yahoo! Research; Deepak Agarwal, Yahoo! Research; Pradheep Elango, Yahoo! Labs

Fast Query Execution for Retrieval Models based on Path Constraint Random Walks
Ni Lao, Carnegie Mellon Univ.; William Cohen, Carnegie Mellon Univ.

Flexible Constrained Spectral Clustering
Xiang Wang, UC Davis; Ian Davidson, UC Davis

Frequent Regular Itemset Mining
Salvatore Ruggieri, Università di Pisa

GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection
Feng Chen, Virginia Tech; Chang-Tien Lu, Virginia Tech

Grafting-Light: Fast, Incremental Feature Selection and Structure Learning of Markov Random Fields
Jun Zhu, Carnegie Mellon Univ.; Ni Lao, Carnegie Mellon Univ.; Eric Xing, Carnegie Mellon Univ.

Growing a tree in the forest: constructing folksonomies by integrating structured metadata
Anon Plangprasopchok, Information Sciences Institute, Univ. of Southern California; Kristina Lerman, Univ. of Southern California; Lise Getoor, University of Maryland, College Park

Inferring Networks of Diffusion and Influence
Manuel Gomez Rodriguez, Stanford University; Jure Leskovec, Stanford University; Andreas Krause, California Institute of Technology

k-Support Anonymity based on Pseudo Taxonomy for Outsourcing of Frequent Itemset Mining
Chih-Hua Tai, Ntu; Philip Yu, University of Illinois at Chicago; Ming-Syan Chen, National Taian University

Large Linear Classification When Data Cannot Fit In Memory
Hsiang-Fu Yu, National Taiwan University; Cho-Jui Hsieh , ; Kai-Wei Chang, ; Chih-Jen Lin, National Taiwan University

Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
Jianhui Chen, Arizona State University; Ji Liu, Arizona State University; Jieping Ye, Arizona State University

Learning to Combine Discriminative Classifiers
Chi-Hoon Lee, Yahoo! Labs

Learning with Cost Intervals
Xu-Ying Liu, Nanjing University; Zhi-Hua Zhou, Nanjing University

Mass Estimation and Its Applications
Kai Ming Ting, Monash University; Guang-Tong Zhou, Shandong University; Fei Tony LIU, Monash University; James Tan, Monash University

Mining Advisor-Advisee Relationships from Research Publication Networks
Chi Wang, Univ. of Illinois, Urbana Champaign; Jiawei Han, Univ. of Illinois, Urbana Champaign; Yuntao Jia, Univ. of Illinois, Urbana Champaign; Jie Tang, Tsinghua Univ.; Duo Zhang, Univ. of Illinois, Urbana Champaign; Yintao Yu, Univ. of Illinois, Urbana Champaign; Jingyi Guo, Tsinghua Univ.

Mining Hidden Periodic Behaviors for Moving Objects
Zhenhui Li, University of Illinois at Urbana-Champaign; Bolin Ding, University of Illinois at Urbana-Champaign; Jiawei Han, University of Illinois at Urbana-Champaign; Roland Kays, New York State Museum

Mining Positive and Negative Patterns for Relevance Feature Discovery
Yuefeng Li, Queensland University of Technology; Abdulmohsen Algarni, Queensland University of Technology; Ning Zhong, Maebashi Institute of Technology, Japan

Mining Program Workflow from Interleaved Traces
Jian-Guang LOU, Microsoft Research Asia; Qiang FU, Microsoft Research Asia; Shengqi YANG, Beijing Univ. of Posts and Telecom; Jiang LI, Microsoft Research Asia; Bin WU, Beijing Univ. of Posts and Telecom

Mining Top-K Frequent Items in a Data Stream with Flexible Sliding Windows
Hoang Thanh Lam, Technische Universiteit Eindhoven; Toon Calders, Technische Universiteit Eindhoven

Mining Uncertain Data with Probabilistic Guarantees
Liwen Sun, University of Hong Kong; Reynold Cheng, University of Hong Kong; David Cheung, University of Hong Kong; Jiefeng Cheng, University of Hong Kong

Modeling Relational Events via Latent Classes
Christopher DuBois, UC Irvine; Padhraic Smyth, UC Irvine

Multi-Label Learning by Exploiting Label Dependency
Min-Ling Zhang, Hohai University, China; Kun Zhang, MPI for Biological Cybernetics

Multi-Task Learning for Boosting with Application to Web Search Ranking
Olivier Chapelle, Yahoo! Research; Srinivas Vadrevu, Yahoo! Labd; Kilian Weinberger, Washington University in St. Louis; Pannagadatta Shivaswamy, Columbia University; Ya Zhang, Shanghai Jiaotong University; Belle Tseng, Yahoo! Labs

Negative correlations in collaboration: concepts and algorithms
Jinyan Li, Nanyang Technological University, Singapore; Qian Liu, Nanyang Technological University, Singapore; Tao Zeng, Nanyang Technological University, Singapore

Neighbor Query Friendly Compression of Social Networks
Hossein Maserrat, Simon Fraser University; Jian Pei, Simon Fraser University

Nonnegative Shared Subspace Learning and Its Application to Social Media Retrieval
Sunil Gupta, Curtin University; Dinh Phung, Curtin University; Brett Adams, Curtin University; Truyen Tran, Curtin University; Svetha Venkatesh, Curtin University

On the Quality of Inferring Interests From Social Neighbors
Zhen Wen, IBM T.J. Watson Research; Ching-Yung Lin, IBM T.J. Watson Research Center

Online Discovery and Maintenance of Time Series Motifs
Abdullah Mueen, UC Riverside; Eamonn Keogh, UC Riverside

Online Multiscale Dynamic Topic Models
Tomoharu Iwata, ; Takeshi Yamada, NTT; Yasushi Sakurai, NTT; Naonori Ueda, NTT

Privacy-Preserving Outsourcing Support Vector Machines with Random Transformation
Keng-Pei Lin, National Taiwan University; Ming-Syan Chen, National Taiwan University

Redefining Class Definitions using Constraint-Based Clustering
Dan Preston, Tufts University; Carla Brodley, Tufts University; Roni Khardon, Tufts University; Damien Sulla-Menashe, Boston University; Mark Friedl, Boston University

Scalable Influence Maximization for Prevalent Viral Marketing in Large-Scale Social Networks
Wei Chen, Microsoft Research Asia; Chi Wang, Univ. of Illinois, Urbana Champaign; Yajun Wang, Microsoft Research Asia

Scalable Similarity Search with Optimized Kernel Hashing
Junfeng He, Columbia University; Wei Liu, Columbia University; Shih-Fu Chang, Columbia University

Semi-Supervised Sparse Metric Learning Using Alternating Linearization Optimization
Wei Liu, Chinese University of Hong Kong; Shiqian Ma, Columbia University; Dacheng Tao, Nanyang Technological University, Singapore; Peng Liu, Stevens Institute of Technology; Jianzhuang Liu, Chinese University of Hong Kong

Semi-supervised Feature Selection for Graph Classification
Xiangnan Kong, University of Illinois at Chicago; Philip Yu, University of Illinois at Chicago

Suggesting Friends Using the Implicit Social Graph
Maayan Roth, Google; Assaf Ben-David, Google; David Deutscher, Google, Inc; Guy Flysher, Google, Inc; Ilan Horn, Google, Inc; Aril Leichtberg, Google; Naty Leiser, Google ; Ron Merom, Google; Yossi Mattias, Google, Inc

The community-search problem and how to plan a successful cocktail party
Mauro Sozio, Max-Planck-Institut fur Informatik; Aristides Gionis, Yahoo! Research Barcelona

The new Iris Data: Modular Data Generators
Iris Adae, Universitaet Konstanz; Michael Berthold, University of Konstanz

The Topic-Perspective Model for Social Tagging Systems
Caimei Lu, Drexel University; Xiaohua Hu, Drexel University; Xin Chen, Drexel University; Jung-ran Park, Drexel University

Topic Dynamics: an alternative model of 'Bursts' in Streams of Topics
Dan He, UCLA; Douglass Parker, UCLA

Topic Models with Power-Law Using Pitman-Yor Process
Issei Sato, University of Tokyo; Hiroshi Nakagawa, University of Tokyo

Training and Testing of Recommender Systems on Data Missing Not at Random
Harald Steck, Bell Labs, Alcatel-Lucent

Trust Network Inference for Online Rating Data Using Generative Models
Freddy Chong Tat Chua, Singapore Management Universit; Ee-Peng Lim, Singapore Management University

Unifying Dependent Clustering and Disparate Clustering for Non-homogeneous Data
M. Shahriar Hossain, Virginia Tech; Satish Tadepalli, Virginia Tech; Layne Watson, Virginia Tech; Ian Davidson, UC Davis; Richard Helm, Virginia Tech; Naren Ramakrishnan, Virginia Tech

Unsupervised Feature Selection for Multi-Cluster Data
Deng Cai, Zhejiang University; Chiyuan Zhang, Zhejiang University; Xiaofei He, Zhejiang University

Unsupervised Transfer Learning: Application to Text Categorization
Tianbao Yang, Michigan State University; Rong Jin, Michigan State University; Anil Jain, Michigan State University; Yang Zhou, Michigan State University; Wei Tong, Michigan State University

UP-Growth: An Efficient Algorithm for High Utility Itemsets Mining
Vincent Tseng, National Cheng Kung University; Cheng Wei Wu, National Cheng Kung University; Bai-En Shie, National Cheng Kung University; Philip Yu, University of Illinois at Chicago

User Browsing Models: Relevance versus Examination
Ramakrishnan Srikant, Google Research; Sugato Basu, Google Research; Ni Wang, Google; Daryl Pregibon, Google

Versatile Publishing for Privacy Preservation
Xin Jin, George Washington University; Mingyang Zhang, George Washington University; Nan Zhang, George Washington University; Gautum Das, University of Texas, Arlington

Why label when you can search? Strategies for applying human resources to build classification models under extreme class imbalance.
Josh Attenberg, NYU Polytechnic Institute; Foster Provost, NYU

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Mixture Models for Learning Low-dimensional Roles in High-dimensional Data
Manas Somaiya, University of Florida; Christopher Jermaine, Rice University; Sanjay Ranka, University of Florida

A Probabilistic Model for Personalized Tag Prediction
Dawei Yin, Lehigh University; Zhenzhen Xue, Lehigh University; Liangjie Hong, Lehigh University; Brian Davison, Lehigh University

A Unified Algorithmic Framework for Multi-Dimensional Scaling
Arvind Agarwal, University of Utah; Jeff Phillips, University of Utah; Suresh Venkatasubramanian, University of Utah

BioSnowball: Automated Population of Wikis
Xiaojiang Liu, USTC, China; Zaiqing Nie, Microsoft Research Aisa; Nenghai Yu, USTC, China; Ji-Rong Wen, Microsoft Research Asia

Boosting with Structure Information in the Functional Space: an Application to Graph Classification
Hongliang Fei, University of Kansas; Jun Huan, University of Kansas

Cold Start Link Prediction
Vincent Leroy, IRISA; B. Barla Cambazoglu, Yahoo! Research; Francesco Bonchi, Yahoo! Research

Community-based Greedy Algorithm for Mining Top-K Influential Nodes in Mobile Social Networks
Yu Wang, Peking University; Gao Cong, Nanyang Techonological University; Guojie Song, Peking University; Kunqing Xie, Peking University

Direct Mining of Discriminative Patterns for Classifying Uncertain Data
Chuancong Gao, Tsinghua University; Jianyong Wang, Tsinghua University

Discovering Probabilistic Frequent Subgraphs over Uncertain Graph Databases
Zhaonian Zou, Harbin Institute of Technology; Jianzhong Li, Harbin Institute of Technology; Hong Gao, Harbin Institute of Technology

DivRank: the Interplay of Prestige and Diversity in Information Networks
Qiaozhu Mei, University of Michigan; Jian Guo, University of Michigan; Dragomir Radev, University of Michigan

Dynamics of Conversations
Ravi Kumar, Yahoo; Mohammad Mahdian, Yahoo! Research; Mary McGlohon, Carnegie Mellon Univ.

Ensemble Pruning via Individual Contribution Ordering
Zhenyu Lu, University of Vermont; Xindong Wu, University of Vermont; Josh Bongard, University of Vermont

Feature Selection for Support Vector Regression Using Probabilistic Prediction
Chong-Jin Ong, National University Singapore; Jianbo Yang, National University Singapore

Finding Effectors in Social Networks
Theodoros Lappas, Univ. of California, Riverside; Heikki Mannila, University of Helsinki; Evimaria Terzi, Boston University; Dimitrios Gunopulos, University of Athens

Generative Models for Ticket Resolution in Expert Networks
Gengxin Miao, University of California at Santa Barbara; Louise Moser, University of California at Santa Barbara; Xifeng Yan, University of California at Santa Barbara; Shu Tao, IBM T. J. Watson; Yi Chen, Arizona State Univ.; Nikos Anerousis, IBM T. J. Watson

Latent Aspect Rating Analysis on Review Text Data: A Rating Regression Approach
Hongning Wang, University of Illinois at Urbana-Champaign; Yue Lu, University of Illinois at Urbana-Champaign; ChengXiang Zhai, University of Illinois at Urbana-Champaign

New Perspectives and Methods in Link Prediction
Ryan Lichtenwalter, The University of Notre Dame; Jake Lussier, The University of Notre Dame; Nitesh Chawla, The University of Notre Dame

Parallel SimRank Computation on Large Graphs with Iterative Aggregation
Guoming He, Renmin University of China; Haijun Feng, Renmin University of China; Cuiping Li, Renmin University of China; Hong Chen, Renmin University of China

Probably the Best Itemsets
Nikolaj Tatti, University of Antwerp

Semantic Relation Extraction With Kernels Over Typed Dependency Trees
Frank Reichartz, Fraunhofer IAIS, Germany; hannes Korte, Fraunhofer IAIS, Germany; Gerd Paass, Fraunhofer IAIS, Germany

Social Action Tracking via Noise Tolerant Time-varying Factor Graphs
Chenhao Tan, Tsinghua University; Jie Tang, Tsinghua; Jimeng Sun, IBM; Quan Lin, Huazhong University of Science and Technology; Fengjiao Wang, BeiJing University of Aeronautics & Astronautics

Temporal Recommendation on Graphs via Long- and Short-term Preference Fusion
Liang Xiang, Institute of Automation, Chinese Academy of Sciences; Quan Yuan, IBM Research - China; Shiwan Zhao, IBM Research - China; Li Chen, Department of Computer Science, Hong Kong Baptist University; Xiatian Zhang, IBM Research - China; Jimeng Sun, IBM

Towards Mobility-based Clustering
Siyuan Liu, Hong Kong UST; Yunhuai Liu, Hong Kong UST; Lionel Ni, Hong Kong UST; Jianping Fan, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Minglu Li, Shanghai Jiaotong University

Transfer Metric Learning by Learning Task Relationships
Yu Zhang, Hong Kong UST; Dit-Yan Yeung, Hong Kong UST

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Data Mining to Predict and Prevent Errors in Health Insurance Claims Processing
Mohit Kumar*, Accenture Technology Labs; Rayid Ghani, Accenture Technology Labs; Zhu-Song Mei, Accenture Technology Labs

TIARA: A Visual Exploratory Text Analytic System
Furu Wei*, IBM Research - China; Shixia Liu, IBM Research - China; Yangqiu Song, ; Shimei Pan, IBM; Michelle Zhou, IBM Research

MineFleet: An Overview of a Widely Adopted Distributed Vehicle Performance Data Mining System
Hillol Kargupta*, Agnik; Kakali Sarkar, Agnik; Michael Gilligan, Agnik

MetricForensics: A Multi-Level Approach for Mining Volatile Graphs
Tina Eliassi-Rad*, Lawrence Livermore Lab; Keith Henderson, Lawrence Livermore Lab; Christos Faloutsos, CMU; Leman Akoglu, Carnegie Mellon University; Lei Li, Carnegie Mellon University; Koji Maruhashi, Fujitsu Laboratories Ltd.; B. Aditya Prakash, Carnegie Mellon University; Hanghang Tong, Carnegie Mellon University

Evaluating Online Ad Campaigns in a Pipeline: Causal Models At Scale
Diane Lambert*, Google; David Chan, ; Rong Ge, ; Ori Gershony, ; Tim Hesterberg,

Discovery of Significant Emerging Trends
Lyle Ungar*, U. Pennsylvania; Saurabh Goorha, Dow Jones

Overlapping Experiment Infrastructure: More, Better, Faster Experimentation
Diane Tang*, Google; Ashish Agarwal, Google; Deirdre O'Brien, Google; Mike Meyer, Google

Optimizing Debt Collections Using Constrained Reinforcement Learning
Naoki Abe*, IBM T J Watson Research Center; Prem Melville, IBM Research; Cezar Pendus, IBM Research; David Jensen, IBM Research; Chandan Reddy, Wayne State University; Vince Thomas, IBM; James Bennett, IBM; Gary Anderson, IBM

MalStone: Towards A Benchmark for Analytics on Large Data Clouds
Collin Bennett, Open Data Group; Robert Grossman*, Open Data Group; David Locke, Open Data Group; Jonathan Seidman, Open Data Group; Steve Vejcik, Open Data Group

Using Data Mining Techniques to Address Critical Information Exchange Needs in Disaster Affected Public-Private Networks
Li Zheng*, Florida International Univ.; LIANG TANG, Florida International Univ; Chao Shen, ; Tao Li, Florida International University; Steve Luis, ; Shu-Ching Chen, ; Vagelis Hristidis,

Automatic Malware Categorization Using Cluster Ensemble
Yanfang Ye, Xiamen University; Tao Li*, Florida International University; Yong Chen, Kingsoft Corporation

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Beyond Heuristics: Learning to Classify Vulnerabilities and Predict Exploits
Mehran Bozorgi*, UCSD; Lawrence Saul, UCSD; Stefan Savage, UCSD; Geoffrey Voelker, UCSD

Tropical Cyclone Event Sequence Similarity Search via Dimensionality Reduction and Metric Learning
Shen-Shyang Ho*, Caltech/JPL; Wenqing Tang, ; W. Timothy Liu,

Active Learning for Biomedical Citation Screening
Byron Wallace*, Tufts ; Kevin Small, Tufts; Carla Brodley, Tufts University; Thomas Trikalinos, Tufts Medical Center

Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study
Santanu Das*, UARC, UCSC; bryan Matthews, ; Ashok Srivastava, ; Nikunj Oza, NASA Ames Research Center

Diagnosing Memory Leaks using Graph Mining on Heap Dumps
Evan Maxwell, Virginia Tech; Godmar Back, Virginia Tech; Naren Ramakrishnan*, Virginia Tech

Medical Coding Classification by Leveraging Inter-Code Relationships
Yan Yan, Northeastern University; Glenn Fung, SIEMENS; Jennifer Dy, Northeaster; Romer Rosales*, SIEMENS

Detecting Abnormal Coupled Sequences and Sequence Changes in Group-based Manipulative Trading Behaviors
Longbing Cao*, UST, Australia; Yuming Ou, University of Technology Sydney; Philip Yu, University of Illinois at Chicago; Gang Wei, Shanghai Stock Exchange

Exploitation and Exploration in a Performance based Contextual Advertising System
Wei Li, Yahoo! Labs; Xuerui Wang, Yahoo! Labs; Ruofei Zhang*, Yahoo! Labs; Ying Cui, Yahoo! Labs; Rong Jin, Michigan State Univerisity; Jianchang Mao, Yahoo! Labs

An Integrated Machine Learning Approach to Stroke Prediction
Yu Cao*, ; Aditya Khosla, ; Cliff Lin, ; Hsu-Kuang Chiu, ; Honglak Lee, Stanford University; Junling Hu,

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The 16^th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2010) will be held on July 25-28, 2010 in Crystal City, Washington, DC. The conference will include two refereed paper tracks:

• the Research track, and
• the Industry & Government track

1. To submit your paper to either the Research track or the Industrial track, please log into the Submission Server.
2. Abstracts are due Feb 2, 2010 at 11:59 PM Pacific time.
3. Papers are due Feb 5, 2010 at 11:59 PM Pacific time.
4. All papers should adhere to the ACM proceedings template. Papers are allowed at most ten (10) full pages, including all figures, tables, references and appendix (if any).
5. The papers will *not* be reviewed double-blind. Please include your name and affiliation in the submission, as well as full references to your relevant prior work.
6. Submissions that deviate from these guidelines may be rejected without consideration. Out of fairness to other authors, we are not able to grant extensions or accept late submissions.