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11th ICDM 2011: Vancouver, BC, Canada
- Diane J. Cook, Jian Pei, Wei Wang, Osmar R. Zaïane, Xindong Wu:
11th IEEE International Conference on Data Mining, ICDM 2011, Vancouver, BC, Canada, December 11-14, 2011. IEEE Computer Society 2011, ISBN 978-0-7695-4408-3
Regular Papers
- Rezwan Ahmed, George Karypis:
Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks. 1-10 - Pranay Anchuri, Mohammed J. Zaki, Omer Barkol, Ruth Bergman, Yifat Felder, Shahar Golan, Arik Sityon:
Infrastructure Pattern Discovery in Configuration Management Databases via Large Sparse Graph Mining. 11-20 - Shin Ando, Einoshin Suzuki:
Role-Behavior Analysis from Trajectory Data by Cross-Domain Learning. 21-30 - Hasna Barkia, Haytham Elghazel, Alex Aussem:
Semi-supervised Feature Importance Evaluation with Ensemble Learning. 31-40 - Justin D. Basilico, M. Arthur Munson, Tamara G. Kolda, Kevin R. Dixon, W. Philip Kegelmeyer:
COMET: A Recipe for Learning and Using Large Ensembles on Massive Data. 41-50 - Francesco Bonchi, Aristides Gionis, Antti Ukkonen:
Overlapping Correlation Clustering. 51-60 - Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning. 61-70 - Siddhartha Bhattacharyya:
Confidence in Predictions from Random Tree Ensembles. 71-80 - Petko Bogdanov, Misael Mongiovì, Ambuj K. Singh:
Mining Heavy Subgraphs in Time-Evolving Networks. 81-90 - Xiao Cai, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Multi-Class L2, 1-Norm Support Vector Machine. 91-100 - Nan Cao, David Gotz, Jimeng Sun, Yu-Ru Lin, Huamin Qu:
SolarMap: Multifaceted Visual Analytics for Topic Exploration. 101-110 - Mostafa Haghir Chehreghani:
Efficiently Mining Unordered Trees. 111-120 - Yi-Cheng Chen, Wen-Chih Peng, Suh-Yin Lee:
CEMiner - An Efficient Algorithm for Mining Closed Patterns from Time Interval-Based Data. 121-130 - Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain:
LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction. 131-140 - Avinava Dubey, Indrajit Bhattacharya, Mrinal Kanti Das, Tanveer A. Faruquie, Chiranjib Bhattacharyya:
Learning Dirichlet Processes from Partially Observed Groups. 141-150 - Wouter Duivesteijn, Arno J. Knobbe:
Exploiting False Discoveries - Statistical Validation of Patterns and Quality Measures in Subgroup Discovery. 151-160 - Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel:
An Efficient Greedy Method for Unsupervised Feature Selection. 161-170 - Hongliang Fei, Jun Huan:
Structured Feature Selection and Task Relationship Inference for Multi-task Learning. 171-180 - Yong Ge, Hui Xiong, Chuanren Liu, Zhi-Hua Zhou:
A Taxi Driving Fraud Detection System. 181-190 - Marjan Ghazvininejad, Mostafa Mahdieh, Hamid R. Rabiee, Parisa Khanipour Roshan, Mohammad Hossein Rohban:
Isograph: Neighbourhood Graph Construction Based on Geodesic Distance for Semi-supervised Learning. 191-200 - Christos Giatsidis, Dimitrios M. Thilikos, Michalis Vazirgiannis:
D-cores: Measuring Collaboration of Directed Graphs Based on Degeneracy. 201-210 - Amit Goyal, Wei Lu, Laks V. S. Lakshmanan:
SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model. 211-220 - Siyu Gu, Jun Yan, Lei Ji, Shuicheng Yan, Junshi Huang, Ning Liu, Ying Chen, Zheng Chen:
Cross Domain Random Walk for Query Intent Pattern Mining from Search Engine Log. 221-230 - Stephan Günnemann, Emmanuel Müller, Sebastian Raubach, Thomas Seidl:
Flexible Fault Tolerant Subspace Clustering for Data with Missing Values. 231-240 - T. Ryan Hoens, Nitesh V. Chawla, Robi Polikar:
Heuristic Updatable Weighted Random Subspaces for Non-stationary Environments. 241-250 - Timothy M. Hospedales, Shaogang Gong, Tao Xiang:
Learning Tags from Unsegmented Videos of Multiple Human Actions. 251-259 - Po Hu, Minlie Huang, Peng Xu, Weichang Li, Adam K. Usadi, Xiaoyan Zhu:
Generating Breakpoint-based Timeline Overview for News Topic Retrospection. 260-269 - Hao Huang, Shinjae Yoo, Hong Qin, Dantong Yu:
A Robust Clustering Algorithm Based on Aggregated Heat Kernel Mapping. 270-279 - Xin Jin, W. Scott Spangler, Ying Chen, Keke Cai, Rui Ma, Li Zhang, Xian Wu, Jiawei Han:
Patent Maintenance Recommendation with Patent Information Network Model. 280-289 - Ye Jin, Sriram Lakshminarasimhan, Neil Shah, Zhenhuan Gong, Choong-Seock Chang, Jackie Chen, Stéphane Ethier, Hemanth Kolla, Seung-Hoe Ku, Scott Klasky, Robert Latham, Robert B. Ross, Karen Schuchardt, Nagiza F. Samatova:
S-preconditioner for Multi-fold Data Reduction with Guaranteed User-Controlled Accuracy. 290-299 - U Kang, Christos Faloutsos:
Beyond 'Caveman Communities': Hubs and Spokes for Graph Compression and Mining. 300-309 - Anitha Kannan, Partha Pratim Talukdar, Nikhil Rasiwasia, Qifa Ke:
Improving Product Classification Using Images. 310-319 - Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik:
Learning Markov Logic Networks via Functional Gradient Boosting. 320-329 - Hyungsul Kim, Sungjin Im, Tarek F. Abdelzaher, Jiawei Han, David Sheridan, Shobha Vasudevan:
Signature Pattern Covering via Local Greedy Algorithm and Pattern Shrink. 330-339 - Younghoon Kim, Kyuseok Shim:
TWITOBI: A Recommendation System for Twitter Using Probabilistic Modeling. 340-349 - Kleanthis-Nikolaos Kontonasios, Jilles Vreeken, Tijl De Bie:
Maximum Entropy Modelling for Assessing Results on Real-Valued Data. 350-359 - Florian Lemmerich, Frank Puppe:
Local Models for Expectation-Driven Subgroup Discovery. 360-369 - Bing Li, Weihua Xiong, Weiming Hu:
Context-Aware Multi-instance Learning Based on Hierarchical Sparse Representation. 370-377 - Cindy Xide Lin, Qiaozhu Mei, Jiawei Han, Yunliang Jiang, Marina Danilevsky:
The Joint Inference of Topic Diffusion and Evolution in Social Communities. 378-387 - Dong Liu, Shuicheng Yan, Yadong Mu, Xian-Sheng Hua, Shih-Fu Chang, Hong-Jiang Zhang:
Towards Optimal Discriminating Order for Multiclass Classification. 388-397 - Haishan Liu, Paea LePendu, Ruoming Jin, Dejing Dou:
A Hypergraph-based Method for Discovering Semantically Associated Itemsets. 398-406 - Qi Liu, Yong Ge, Zhongmou Li, Enhong Chen, Hui Xiong:
Personalized Travel Package Recommendation. 407-416 - Yang Liu, Fei Wu, Yin Zhang, Jian Shao, Yueting Zhuang:
Tag Clustering and Refinement on Semantic Unity Graph. 417-426 - Cheng Long, Raymond Chi-Wing Wong:
Minimizing Seed Set for Viral Marketing. 427-436 - Nigel Medforth, Ke Wang:
Privacy Risk in Graph Stream Publishing for Social Network Data. 437-446 - Pauli Miettinen:
Boolean Tensor Factorizations. 447-456 - Emilie Morvant, Amaury Habrard, Stéphane Ayache:
Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions. 457-466 - Masud Moshtaghi, Christopher Leckie, Shanika Karunasekera, James C. Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Incremental Elliptical Boundary Estimation for Anomaly Detection in Wireless Sensor Networks. 467-476 - Quang Nguyen, Hamed Valizadegan, Milos Hauskrecht:
Learning Classification with Auxiliary Probabilistic Information. 477-486 - Tam T. Nguyen, Kuiyu Chang, Siu Cheung Hui:
Word Cloud Model for Text Categorization. 487-496 - Xia Ning, George Karypis:
SLIM: Sparse Linear Methods for Top-N Recommender Systems. 497-506 - Jinoh Oh, Sun Park, Hwanjo Yu, Min Song, Seung-Taek Park:
Novel Recommendation Based on Personal Popularity Tendency. 507-516 - Charles Parker:
An Analysis of Performance Measures for Binary Classifiers. 517-526 - Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
Detection of Cross-Channel Anomalies from Multiple Data Channels. 527-536 - B. Aditya Prakash, Deepayan Chakrabarti, Michalis Faloutsos, Nicholas Valler, Christos Faloutsos:
Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks. 537-546 - Thanawin Rakthanmanon, Eamonn J. Keogh, Stefano Lonardi, Scott Evans:
Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data. 547-556 - Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh:
Mining Historical Documents for Near-Duplicate Figures. 557-566 - Teemu Roos, Yuan Zou:
Analysis of Textual Variation by Latent Tree Structures. 567-576 - Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong:
Healing Sample Selection Bias by Source Classifier Selection. 577-586 - C. Seshadhri, Ali Pinar, Tamara G. Kolda:
An In-depth Study of Stochastic Kronecker Graphs. 587-596 - Fanhua Shang, Yuanyuan Liu, Fei Wang:
Learning Spectral Embedding for Semi-supervised Clustering. 597-606 - Junming Shao, Claudia Plant, Qinli Yang, Christian Böhm:
Detection of Arbitrarily Oriented Synchronized Clusters in High-Dimensional Data. 607-616 - Kan Shao, Yandong Liu, Daniel B. Neill:
A Generalized Fast Subset Sums Framework for Bayesian Event Detection. 617-625 - Chao Shen, Tao Li:
Learning to Rank for Query-Focused Multi-document Summarization. 626-634 - Victor S. Sheng:
Simple Multiple Noisy Label Utilization Strategies. 635-644 - Kilho Shin:
Partitionable Kernels for Mapping Kernels. 645-654 - Arnaud Soulet, Chedy Raïssi, Marc Plantevit, Bruno Crémilleux:
Mining Dominant Patterns in the Sky. 655-664 - Michel Speiser, Gianluca Antonini, Abderrahim Labbi:
Ranking Web-Based Partial Orders by Significance Using a Markov Reference Model. 665-674 - Eirini Spyropoulou, Tijl De Bie:
Interesting Multi-relational Patterns. 675-684 - Luite Stegeman, Ad Feelders:
On Generating All Optimal Monotone Classifications. 685-694 - Souhaib Ben Taieb, Gianluca Bontempi:
Recursive Multi-step Time Series Forecasting by Perturbing Data. 695-704 - Nikolaj Tatti, Fabian Moerchen:
Finding Robust Itemsets under Subsampling. 705-714 - Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu:
Density Estimation Based on Mass. 715-724 - Mikalai Tsytsarau, Francesco Bonchi, Aristides Gionis, Themis Palpanas:
Diverse Dimension Decomposition of an Itemset Space. 725-734 - Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht:
Conditional Anomaly Detection with Soft Harmonic Functions. 735-743 - Celine Vens, Fabrizio Costa:
Random Forest Based Feature Induction. 744-753 - Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
Class Imbalance, Redux. 754-763 - Hongxing Wang, Junsong Yuan, Yap-Peng Tan:
Combining Feature Context and Spatial Context for Image Pattern Discovery. 764-773 - Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation. 774-783 - Liaoruo Wang, Tiancheng Lou, Jie Tang, John E. Hopcroft:
Detecting Community Kernels in Large Social Networks. 784-793 - Xuezhi Wang, Jie Tang, Hong Cheng, Philip S. Yu:
ADANA: Active Name Disambiguation. 794-803 - Xufei Wang, Jiliang Tang, Huan Liu:
Document Clustering via Matrix Representation. 804-813 - Zhenxing Wang, Laiwan Chan:
Using Bayesian Network Learning Algorithm to Discover Causal Relations in Multivariate Time Series. 814-823 - Cheng-Wei Wu, Philippe Fournier-Viger, Philip S. Yu, Vincent S. Tseng:
Efficient Mining of a Concise and Lossless Representation of High Utility Itemsets. 824-833 - Rongjing Xiang, Jennifer Neville:
Understanding Propagation Error and Its Effect on Collective Classification. 834-843 - Liang Xiong, Xi Chen, Jeff G. Schneider:
Direct Robust Matrix Factorizatoin for Anomaly Detection. 844-853 - Tengke Xiong, Shengrui Wang, Qingshan Jiang, Joshua Zhexue Huang:
A New Markov Model for Clustering Categorical Sequences. 854-863 - Xiaoran Xu, Zhi-Hong Deng:
BibClus: A Clustering Algorithm of Bibliographic Networks by Message Passing on Center Linkage Structure. 864-873 - Ye Xu, Wei Ping, Andrew T. Campbell:
Multi-instance Metric Learning. 874-883 - Zhao Xu, Kristian Kersting:
Multi-task Learning with Task Relations. 884-893 - Bin Yang, Issei Sato, Hiroshi Nakagawa:
Secure Clustering in Private Networks. 894-903 - Zhijun Yin, Liangliang Cao, Jiawei Han, Chengxiang Zhai, Thomas S. Huang:
LPTA: A Probabilistic Model for Latent Periodic Topic Analysis. 904-913 - Kui Yu, Xindong Wu, Wei Ding, Hao Wang, Hongliang Yao:
Causal Associative Classification. 914-923 - Chao Yuan:
Multi-task Learning for Bayesian Matrix Factorization. 924-931 - Peng Zhang, Byron J. Gao, Xingquan Zhu, Li Guo:
Enabling Fast Lazy Learning for Data Streams. 932-941 - Xianchao Zhang, Quanzeng You:
Clusterability Analysis and Incremental Sampling for Nyström Extension Based Spectral Clustering. 942-951 - Yan-Ming Zhang, Kaizhu Huang, Cheng-Lin Liu:
Fast and Robust Graph-based Transductive Learning via Minimum Tree Cut. 952-961 - Yuchen Zhao, Xiangnan Kong, Philip S. Yu:
Positive and Unlabeled Learning for Graph Classification. 962-971 - Yuhai Zhao, Guoren Wang, Yuan Li, Zhanghui Wang:
Finding Novel Diagnostic Gene Patterns Based on Interesting Non-redundant Contrast Sequence Rules. 972-981 - Li Zheng, Tao Li:
Semi-supervised Hierarchical Clustering. 982-991 - Indre Zliobaite, Faisal Kamiran, Toon Calders:
Handling Conditional Discrimination. 992-1001
Short Papers
- Charu C. Aggarwal, Yao Li, Philip S. Yu:
On the Hardness of Graph Anonymization. 1002-1007 - Hong Cao, Xiaoli Li, David Yew-Kwong Woon, See-Kiong Ng:
SPO: Structure Preserving Oversampling for Imbalanced Time Series Classification. 1008-1013 - Miguel Á. Carreira-Perpiñán, Zhengdong Lu:
Manifold Learning and Missing Data Recovery through Unsupervised Regression. 1014-1019 - Danqi Chen, Weizhu Chen, Qiang Yang:
Characterizing Inverse Time Dependency in Multi-class Learning. 1020-1025 - Pan Du, Jiafeng Guo, Xueqi Cheng:
Supervised Lazy Random Walk for Topic-Focused Multi-document Summarization. 1026-1031 - Wentao Fan, Nizar Bouguila, Djemel Ziou:
Unsupervised Anomaly Intrusion Detection via Localized Bayesian Feature Selection. 1032-1037 - Qiong Fang, Jianlin Feng, Wilfred Ng:
Identifying Differentially Expressed Genes via Weighted Rank Aggregation. 1038-1043 - Chuancong Gao, Jianyong Wang, Qingyan Yang:
Efficient Mining of Closed Sequential Patterns on Stream Sliding Window. 1044-1049 - Jing Gao, Wei Fan, Deepak S. Turaga, Srinivasan Parthasarathy, Jiawei Han:
A Spectral Framework for Detecting Inconsistency across Multi-source Object Relationships. 1050-1055 - Zekai Gao, Yangqiu Song, Shixia Liu, Haixun Wang, Hao Wei, Yang Chen, Weiwei Cui:
Tracking and Connecting Topics via Incremental Hierarchical Dirichlet Processes. 1056-1061 - Wei Guan, Arkadas Ozakin, Alexander G. Gray, Jose Borreguero, Shashi Bhushan Pandit, Anna Jagielska, Liliana Wroblewska, Jeffrey Skolnick:
Learning Protein Folding Energy Functions. 1062-1067 - Dan He, Xingquan Zhu, Douglas Stott Parker Jr.:
How Does Research Evolve? Pattern Mining for Research Meme Cycles. 1068-1073 - Jianjun He, Hong Gu, Shaorui Jiang:
Twin Gaussian Processes for Binary Classification. 1074-1079 - Mohammed M. Al-Hindawi, Kais Allab, Khalid Benabdeslem:
Constraint Selection-Based Semi-supervised Feature Selection. 1080-1085 - Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh:
Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL. 1086-1091 - Zhen Hu, Raj Bhatnagar:
Discovery of Versatile Temporal Subspace Patterns in 3-D Datasets. 1092-1097 - Jens Humrich, Thomas Gärtner, Gemma C. Garriga:
A Fixed Parameter Tractable Integer Program for Finding the Maximum Order Preserving Submatrix. 1098-1103 - Yexi Jiang, Chang-Shing Perng, Tao Li, Rong N. Chang:
ASAP: A Self-Adaptive Prediction System for Instant Cloud Resource Demand Provisioning. 1104-1109 - Prateek Jindal, Dan Roth:
Learning from Negative Examples in Set-Expansion. 1110-1115 - Edward Casey Kenley, Young-Rae Cho:
Entropy-Based Graph Clustering: Application to Biological and Social Networks. 1116-1121 - Saehoon Kim, Seungjin Choi:
Semi-supervised Discriminant Hashing. 1122-1127 - Petr Krajca, Jan Outrata, Vilém Vychodil:
Using Frequent Closed Itemsets for Data Dimensionality Reduction. 1128-1133