11. SDM2011: Mesa, Arizona, USA

Session S1 - Anomalies and Anonymity

• Shin Ando, Einoshin Suzuki, Yoichi Seki, Theerasak Thanongphongphan, Daisuke Hoshino:
  ACE: Anomaly Clustering Ensemble for Multi-perspective Anomaly Detection in Robot Behaviors. 1-12
  
• Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
  Interpreting and Unifying Outlier Scores. 13-24
  
• Roberto J. Bayardo, Biswanath Panda:
  Fast Algorithms for Finding Extremal Sets. 25-34
  
• Chih-Hua Tai, Philip S. Yu, De-Nian Yang, Ming-Syan Chen:
  Structural Diversity for Privacy in Publishing Social Networks. 35-46
  
• Myunghwan Kim, Jure Leskovec:
  The Network Completion Problem: Inferring Missing Nodes and Edges in Networks. 47-58
  

Session S2 - Scientific and Medical Applications

• Fei Wang, Jimeng Sun, Shahram Ebadollahi:
  Integrating Distance Metrics Learned from Multiple Experts and its Application in Inter-Patient Similarity Assessment. 59-70
  
• Ghim-Eng Yap, Ah-Hwee Tan, HweeHwa Pang:
  Learning Feature Dependencies for Noise Correction in Biomedical Prediction. 71-82
  
• Elisa Boari de Lima, Raquel Cardoso de Melo Minardi, Wagner Meira Jr., Mohammed Javeed Zaki:
  Data Integration via Constrained Clustering: An Application to Enzyme Clustering. 83-94
  
• Varun Chandola, Ranga Raju Vatsavai:
  A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series. 95-106
  
• Jaya Kawale, Michael Steinbach, Vipin Kumar:
  Discovering Dynamic Dipoles in Climate Data. 107-118
  

Session S3 - Graph Mining

• U. Kang, Spiros Papadimitriou, Jimeng Sun, Hanghang Tong:
  Centralities in Large Networks: Algorithms and Observations. 119-130
  
• Duen Horng Chau, Carey Nachenberg, Jeffrey Wilhelm, Adam Wright, Christos Faloutsos:
  Large Scale Graph Mining and Inference for Malware Detection. 131-142
  
• Hanghang Tong, Ching-Yung Lin:
  Non-Negative Residual Matrix Factorization with Application to Graph Anomaly Detection. 143-153
  
• Yasuo Tabei, Koji Tsuda:
  Kernel-based Similarity Search in Massive Graph Databases with Wavelet Trees. 154-163
  
• Berkant Savas, Inderjit S. Dhillon:
  Clustered low rank approximation of graphs in information science applications. 164-175
  

Session S4 - Classification

• Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
  Who Should Label What? Instance Allocation in Multiple Expert Active Learning. 176-187
  
• Wei Liu, Sanjay Chawla:
  A Quadratic Mean based Supervised Learning Model for Managing Data Skewness. 188-198
  
• Hao Xia, Steven C. H. Hoi:
  MKBoost: A Framework of Multiple Kernel Boosting. 199-210
  
• Ming-Syan Chen, Keng-Pei Lin:
  Efficient Kernel Approximation for Large-Scale Support Vector Machine Classification. 211-222
  
• Shirish Krishnaj Shevade, Balamurugan P., S. Sundararajan, S. Sathiya Keerthi:
  A Sequential Dual Method for Structural SVMs. 223-234
  

Session S5 - Feature Selection and Dimensionality Reduction

• Esa Junttila, Petteri Kaski:
  Segmented nestedness in binary data. 235-246
  
• Zhengzheng Xing, Jian Pei, Philip S. Yu, Ke Wang:
  Extracting Interpretable Features for Early Classification on Time Series. 247-258
  
• Hao Shao, Einoshin Suzuki:
  Feature-based Inductive Transfer Learning through Minimum Encoding. 259-270
  
• Jing Peng, Guna Seetharaman, Stefan A. Robila, Aparna S. Varde, Wei Fan:
  Chernoff Dimensionality Reduction--Where Fisher Meets FKT. 271-282
  
• Haibing Lu, Jaideep Vaidya, Vijayalakshmi Atluri, Heechang Shin, Lili Jiang:
  Weighted Rank-One Binary Matrix Factorization. 283-294
  

Session S6 - Clustering

• Vineet Chaoji, Geng Li, Hilmi Yildirim, Mohammed Javeed Zaki:
  ABACUS: Mining Arbitrary Shaped Clusters from Large Datasets based on Backbone Identification. 295-306
  
• Parasaran Raman, Jeff M. Phillips, Suresh Venkatasubramanian:
  Spatially-Aware Comparison and Consensus for Clusterings. 307-318
  
• Claudia Plant:
  SONAR: Signal De-mixing for Robust Correlation Clustering. 319-330
  
• Pu Wang, Kathryn B. Laskey, Carlotta Domeniconi, Michael Jordan:
  Nonparametric Bayesian Co-clustering Ensembles. 331-342
  
• Omar Odibat, Chandan K. Reddy:
  A Generalized Framework for Mining Arbitrarily Positioned Overlapping Co-clusters. 343-354
  

Session S7 - Social Network Analysis

• Charu C. Aggarwal, Nan Li:
  On Node Classification in Dynamic Content-based Networks. 355-366
  
• Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee-Peng Lim:
  Predicting Item Adoption Using Social Correlation. 367-378
  
• Wei Chen, Alex Collins, Rachel Cummings, Te Ke, Zhenming Liu, David Rincón, Xiaorui Sun, Yajun Wang, Wei Wei, Yifei Yuan:
  Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate. 379-390
  
• Charu C. Aggarwal, Yan Xie, Philip S. Yu:
  Towards Community Detection in Locally Heterogeneous Networks. 391-402
  
• Santhanakrishnan Anand, Rajarathnam Chandramouli, Koduvayur P. Subbalakshmi:
  Cost of Collaboration vs Individual Effort in Social Networks. 403-413
  

Session S8 - Probabilistic and Statistical Methods

• Nikolaj Tatti:
  Are your Items in Order. 414-425
  
• Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
  Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering. 426-437
  
• Kanishka Bhaduri, Kamalika Das, Chris Giannella:
  Distributed Monitoring of the R2 Statistic for Linear Regression. 438-449
  
• Ramnath Balasubramanyan, William W. Cohen:
  Block-LDA: Jointly modeling entity-annotated text and entity-entity links. 450-461
  
• Oliver Schulte:
  A Tractable Pseudo-Likelihood Function for Bayes Nets Applied to Relational Data. 462-473
  

Session S9 - Text and Web Mining

• Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell:
  Sparse Latent Semantic Analysis. 474-485
  
• Xuan Li, Liang Du, Yi-Dong Shen:
  Graph-Based Marginal Ranking for Update Summarization. 486-497
  
• Himabindu Lakkaraju, Chiranjib Bhattacharyya, Indrajit Bhattacharya, Srujana Merugu:
  Exploiting Coherence for the Simultaneous Discovery of Latent Facets and associated Sentiments. 498-509
  
• Xia Ning, Yanjun Qi:
  Semi-Supervised Convolution Graph Kernels for Relation Extraction. 510-521
  
• Charu C. Aggarwal, Arijit Khan, Xifeng Yan:
  On Flow Authority Discovery in Social Networks. 522-533
  

Session S10 - Frequent Pattern Mining

• Francesco Bonchi, Matthijs van Leeuwen, Antti Ukkonen:
  Characterizing Uncertain Data using Compression. 534-545
  
• Esther Galbrun, Pauli Miettinen:
  From Black and White to Full Colour: Extending Redescription Mining Outside the Boolean World. 546-557
  
• Arno Siebes, Rene Kersten:
  A Structure Function for Transaction Data. 558-569
  
• Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit, Jean-François Boulicaut:
  Multidimensional Association Rules in Boolean Tensors. 570-581
  
• Mahashweta Das, Deepak P, Prasad Deshpande, Ramakrishnan Kannan:
  Fast Rule Mining Over Multi-Dimensional Windows. 582-593
  

Session S11 - Novel Learning Methods

• Wei Ping, Ye Xu, Jianyong Wang, Xian-Sheng Hua:
  FAMER: Making Multi-Instance Learning Better and Faster. 594-605
  
• James R. Foulds, Padhraic Smyth:
  Multi-Instance Mixture Models. 606-617
  
• Xiangnan Kong, Xiaoxiao Shi, Philip S. Yu:
  Multi-Label Collective Classification. 618-629
  
• Nicola Barbieri, Giuseppe Manco, Ettore Ritacco:
  A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data. 630-621
  
• Tuyen N. Huynh, Raymond J. Mooney:
  Online Max-Margin Weight Learning for Markov Logic Networks. 642-651
  

Session S12 - Data Streams and Time Series

• Charu C. Aggarwal:
  On Classification of Graph Streams. 652-663
  
• Michael Hahsler, Margaret H. Dunham:
  Temporal Structure Learning for Clustering Massive Data Streams in Real-Time. 664-675
  
• Niko Vuokko, Petteri Kaski:
  Significance of Patterns in Time Series Collections. 676-686
  
• Nuno Castro, Paulo J. Azevedo:
  Time Series Motifs Statistical Significance. 687-698
  
• Gustavo E. A. P. A. Batista, Xiaoyue Wang, Eamonn J. Keogh:
  A Complexity-Invariant Distance Measure for Time Series. 699-710
  

Short Presentations

• Chun Li, Charu C. Aggarwal, Jianyong Wang:
  On Anonymization of Multi-graphs. 711-722
  
• Frank Eichinger, Christopher Oßner, Klemens Böhm:
  Scalable Software-Defect Localisation by Hierarchical Mining of Dynamic Call Graphs. 723-734
  
• Chih-Chun Chia, Zeeshan Syed:
  Computationally Generated Cardiac Biomarkers: Heart Rate Patterns to Predict Death Following Coronary Attacks. 735-746
  
• Hyungsul Kim, Manish Marwah, Martin F. Arlitt, Geoff Lyon, Jiawei Han:
  Unsupervised Disaggregation of Low Frequency Power Measurements. 747-758
  
• Yasushi Sakurai, Lei Li, Yasuko Matsubara, Christos Faloutsos:
  WindMine: Fast and Effective Mining of Web-click Sequences. 759-770
  
• Yunlong He, Renato Monteiro, Haesun Park:
  A Fast Algorithm for Sparse PCA and a New Sparsity Control Criteria. 771-782
  
• Bin Tong, Junbin Gao, Nguyen Huy Thach, Einoshin Suzuki:
  Gaussian Process for Dimensionality Reduction in Transfer Learning. 783-794
  
• Evgeni Tsivtsivadze, Josef Urban, Herman Geuvers, Tom Heskes:
  Semantic Graph Kernels for Automated Reasoning. 795-803
  
• Koen Smets, Jilles Vreeken:
  The Odd One Out: Identifying and Characterising Anomalies. 804-815
  
• Santanu Das, Nikunj C. Oza:
  Sparse Solutions for Single Class SVMs: A Bi-Criterion Approach. 816-827
  
• Pratik Jawanpuria, Jagarlapudi Saketha Nath:
  Multi-task Multiple Kernel Learning. 828-838
  
• Shivani Agarwal:
  The Infinite Push: A New Support Vector Ranking Algorithm that Directly Optimizes Accuracy at the Absolute Top of the List. 839-850
  
• Jun Du, Charles X. Ling:
  Active Teaching for Inductive Learners. 851-861
  
• Ling Chen, Chengqi Zhang:
  Semi-supervised Variable Weighting for Clustering. 862-871
  
• Vinayaka Pandit, Sreyash Kenkre, Arindam Khan:
  Discovering Bucket Orders from Data. 872-883
  
• Kewei Tu, Xixiu Ouyang, Dingyi Han, Vasant Honavar:
  Exemplar-based Robust Coherent Biclustering. 884-895
  
• Rikiya Takahashi:
  Sequential Minimal Optimization in Adaptive-Bandwidth Convex Clustering. 896-907
  
• Fei Wang, Ping Li, Arnd Christian König:
  Efficient Document Clustering via Online Nonnegative Matrix Factorizations. 908-919
  
• Yi Zhang, Tao Li:
  Extending Consensus Clustering to Explore Multiple Clustering Views. 920-931
  
• Nikola Mueller, Katrin Haegler, Junming Shao, Claudia Plant, Christian Böhm:
  Weighted Graph Compression for Parameter-free Clustering With PaCCo. 932-943
  
• Fei Wang, Jimeng Sun, Jianying Hu, Shahram Ebadollahi:
  iMet: Interactive Metric Learning in Healthcare Applications. 944-955
  
• Charanpal Dhanjal, Stéphan Clémençon:
  Maximising the Quality of Influence. 956-967
  
• Pedro Olmo Vaz de Melo, Christos Faloutsos, Antonio Alfredo Ferreira Loureiro:
  Human Dynamics in Large Communication Networks. 968-879
  
• Zhijun Yin, Liangliang Cao, Jiawei Han, Jiebo Luo, Thomas S. Huang:
  Diversified Trajectory Pattern Ranking in Geo-tagged Social Media. 980-991
  
• Bo Liu, Yanshan Xiao, Longbing Cao, Philip S. Yu:
  One-Class-Based Uncertain Data Stream Learning. 992-1003
  
• Hoang Thanh Lam, Toon Calders, Ninh Pham:
  Online Discovery of Top-k Similar Motifs in Time Series Data. 1004-1015
  

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