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ORCID12th SDM 2012: Anaheim, California, USA
- Proceedings of the Twelfth SIAM International Conference on Data Mining, Anaheim, California, USA, April 26-28, 2012. SIAM / Omnipress 2012, ISBN 978-1-61197-232-0
Session CP1 - Applications - Climate and Geography
- James Rosswog, Kanad Ghose:
Detecting and Tracking Coordinated Groups in Dense, Systematically Moving, Crowds. 1-11 - Rikiya Takahashi, Takayuki Osogami, Tetsuro Morimura:
Large-Scale Nonparametric Estimation of Vehicle Travel Time Distributions. 12-23 - Qiang Fu, Arindam Banerjee, Stefan Liess
, Peter K. Snyder:
Drought Detection of the Last Century: An MRF-based Approach. 24-34 - Saurabh V. Pendse, Isaac K. Tetteh, Fredrick H. M. Semazzi, Vipin Kumar, Nagiza F. Samatova:
Toward Data-driven, Semi-automatic Inference of Phenomenological Physical Models: Application to Eastern Sahel Rainfall. 35-46 - Soumyadeep Chatterjee, Karsten Steinhaeuser, Arindam Banerjee, Snigdhansu Chatterjee, Auroop R. Ganguly:
Sparse Group Lasso: Consistency and Climate Applications. 47-58
Session CP2 - Clustering
- Charu C. Aggarwal:
The Multi-Set Stream Clustering Problem. 59-69 - Tantan Liu, Gagan Agrawal:
Stratification Based Hierarchical Clustering Over a Deep Web Data Source. 70-81 - Nikolaos M. Freris, Michail Vlachos, Deepak S. Turaga:
Cluster-Aware Compression with Provable K-means Preservation. 82-93 - Mihajlo Grbovic, Nemanja Djuric, Slobodan Vucetic:
Supervised Clustering of Label Ranking Data. 94-105 - Da Kuang, Haesun Park, Chris H. Q. Ding:
Symmetric Nonnegative Matrix Factorization for Graph Clustering. 106-117
Session - CP3 - Social Media
- Jiliang Tang, Huan Liu:
Feature Selection with Linked Data in Social Media. 118-128 - Ting Wang, Mudhakar Srivatsa, Dakshi Agrawal, Ling Liu:
Microscopic Social Influence. 129-140 - Xutao Li, Michael K. Ng, Yunming Ye:
HAR: Hub, Authority and Relevance Scores in Multi-Relational Data for Query Search. 141-152 - Manish Gupta, Peixiang Zhao, Jiawei Han:
Evaluating Event Credibility on Twitter. 153-164 - Amita Gajewar, Atish Das Sarma:
Multi-skill Collaborative Teams based on Densest Subgraphs. 165-176
Session CP4 - Multi-Source and Multi-Task
- Jaegul Choo, Shawn Bohn, Grant Nakamura, Amanda M. White, Haesun Park:
Heterogeneous Data Fusion via Space Alignment Using Nonmetric Multidimensional Scaling. 177-188 - Neta Rabin, Ronald R. Coifman:
Heterogeneous Datasets Representation and Learning using Diffusion Maps and Laplacian Pyramids. 189-199 - Sunil Kumar Gupta, Dinh Quoc Phung, Svetha Venkatesh:
A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources. 200-211 - Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbonell:
Adaptive Multi-task Sparse Learning with an Application to fMRI Study. 212-223 - Xiaoxiao Shi, Jean-François Paiement, David Grangier, Philip S. Yu:
Learning from Heterogeneous Sources via Gradient Boosting Consensus. 224-235
Session CP5 - Pattern Mining
- Koen Smets, Jilles Vreeken:
Slim: Directly Mining Descriptive Patterns. 236-247 - Boris Cule, Nikolaj Tatti, Bart Goethals:
MARBLES: Mining Association Rules Buried in Long Event Sequences. 248-259 - Anton Dries, Siegfried Nijssen:
Mining Patterns in Networks using Homomorphism. 260-271 - Jana Schmidt, Sonja Ansorge, Stefan Kramer:
Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering. 272-283 - Henrik Grosskreutz:
Class Relevant Pattern Mining in Output-Polynomial Time. 284-294
Session CP6 - Time Series and Sequence Analysis
- Kristian Kersting, Mirwaes Wahabzada, Christoph Römer, Christian Thurau, Agim Ballvora, Uwe Rascher, Jens Leon, Christian Bauckhage, Lutz Plümer:
Simplex Distributions for Embedding Data Matrices over Time. 295-306 - Anthony J. Bagnall, Luke M. Davis, Jon Hills, Jason Lines:
Transformation Based Ensembles for Time Series Classification. 307-318 - Hoang Thanh Lam, Fabian Moerchen, Dmitriy Fradkin, Toon Calders:
Mining Compressing Sequential Patterns. 319-330 - Samuel J. Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
Beam Methods for the Profile Hidden Markov Model. 331-342 - Nikolaos M. Freris, Michail Vlachos, Suleyman Serdar Kozat:
Optimal Distance Estimation Between Compressed Data Series. 343-354
Session CP7 - Kernels and Classification
- Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang:
Multi-Objective Multi-Label Classification. 355-366 - Mehmet Gönen:
Bayesian Supervised Multilabel Learning with Coupled Embedding and Classification. 367-378 - Salvatore Ruggieri:
Subtree Replacement in Decision Tree Simplification. 379-390 - Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray:
A Distributed Kernel Summation Framework for General-Dimension Machine Learning. 391-402 - Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guillermo Sapiro:
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information. 403-414
CP8 - Social Media and Graphs
- Charu C. Aggarwal, Yan Xie, Philip S. Yu:
On Dynamic Link Inference in Heterogeneous Networks. 415-426 - Vatche Ishakian, Dóra Erdös, Evimaria Terzi, Azer Bestavros:
A Framework for the Evaluation and Management of Network Centrality. 427-438 - Leman Akoglu, Hanghang Tong, Brendan Meeder, Christos Faloutsos:
PICS: Parameter-free Identification of Cohesive Subgroups in Large Attributed Graphs. 439-450 - Bing Tian Dai, Freddy Chong Tat Chua, Ee-Peng Lim:
Structural Analysis in Multi-Relational Social Networks. 451-462 - Xinran He, Guojie Song, Wei Chen, Qingye Jiang:
Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model. 463-474
Session - CP9 - Feature Selection, Networks and Prediction
- Jacob Kogan:
Feature Selection over Distributed Data Streams through Convex Optimization. 475-484 - George Forman:
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable. 485-493 - Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrecht:
Sampling Strategies to Evaluate the Performance of Unknown Predictors. 494-505 - Huijing Jiang, Aurélie C. Lozano, Fei Liu:
A Bayesian Markov-switching Model for Sparse Dynamic Network Estimation. 506-515 - Chi Wang, Jiawei Han, Qi Li, Xiang Li, Wen-Pin Lin, Heng Ji:
Learning Hierarchical Relationships among Partially Ordered Objects with Heterogeneous Attributes and Links. 516-527
Session CP10 - Transfer Learning
- Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Transfer Learning of Distance Metrics by Cross-Domain Metric Sampling across Heterogeneous Spaces. 528-539 - Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei Cheng, Xiang Zhang, Wei Wang:
Dual Transfer Learning. 540-551 - Xiaoxiao Shi, Xiangnan Kong, Philip S. Yu:
Transfer Significant Subgraphs across Graph Databases. 552-563 - Jeon-Hyung Kang, Jun Ma, Yan Liu:
Transfer Topic Modeling with Ease and Scalability. 564-575
Session CP11 - Applications - Healthcare and Networks
- Dijun Luo, Fei Wang, Jimeng Sun, Marianthi Markatou, Jianying Hu, Shahram Ebadollahi:
SOR: Scalable Orthogonal Regression for Low-Redundancy Feature Selection and its Healthcare Applications. 576-587 - Jesin Zakaria, Sarah Rotschafer, Abdullah Mueen, Khaleel Razak, Eamonn J. Keogh:
Mining Massive Archives of Mice Sounds with Symbolized Representations. 588-599 - Lu-An Tang, Quanquan Gu, Xiao Yu, Jiawei Han, Thomas La Porta, Alice Leung, Tarek F. Abdelzaher, Lance M. Kaplan:
IntruMine: Mining Intruders in Untrustworthy Data of Cyber-physical Systems. 600-611 - Rong-Hua Li, Jeffrey Xu Yu, Xin Huang, Hong Cheng:
Robust Reputation-Based Ranking on Bipartite Rating Networks. 612-623
Short Presentations
- Charu C. Aggarwal, Karthik Subbian:
Event Detection in Social Streams. 624-635 - Charu C. Aggarwal, Shuyang Lin, Philip S. Yu:
On Influential Node Discovery in Dynamic Social Networks. 636-647 - Faris Alqadah, Joel S. Bader, Rajul Anand, Chandan K. Reddy:
Query-based Biclustering using Formal Concept Analysis. 648-659 - Mohammad Taha Bahadori, Yan Liu:
Granger Causality Analysis in Irregular Time Series. 660-671 - Xue Bai, Zezhen Lin, Yun Xiong, Yangyong Zhu:
Clustering Based on Yukawa Potential. 672-683 - Christian Thurau, Kristian Kersting, Christian Bauckhage:
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study. 684-695 - Mustafa Bilgic:
Combining Active Learning and Dynamic Dimensionality Reduction. 696-707 - Jidong Chen, Wentao Wu, Hang Guo, Wei Wang:
Context-aware Search for Personal Information Management Systems. 708-719 - Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee-Peng Lim:
Mining Social Dependencies in Dynamic Interaction Networks. 720-731 - Weishan Dong, Xin Zhang, Li Li, Changhua Sun, Lei Shi, Wei Sun:
Detecting Irregularly Shaped Significant Spatial and Spatio-Temporal Clusters. 732-743 - Erheng Zhong, Wei Fan, Qiang Yang:
Contextual Collaborative Filtering via Hierarchical Matrix Factorization. 744-755 - Nicola Barile, Ad Feelders:
Active Learning with Monotonicity Constraints. 756-767 - Liang Ge, Aidong Zhang:
Pseudo Cold Start Link Prediction with Multiple Sources in Social Networks. 768-779 - Yangpai Liu, Huiping Cao, Yifan Hao, Peng Han, Xinda Zeng:
Discovering Context-aware Influential Objects. 780-791 - Yuan Hao, Bilson J. L. Campana, Eamonn J. Keogh:
Monitoring and Mining Insect Sounds in Visual Space. 792-803 - Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh:
Image Mining of Historical Manuscripts to Establish Provenance. 804-815 - Yoshitaka Kameya, Taisuke Sato:
RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising. 816-827 - U Kang, Hanghang Tong, Jimeng Sun:
Fast Random Walk Graph Kernel. 828-838 - Jaya Kawale, Aditya Pal, Rob Fatland:
Tracking Spatio-Temporal Diffusion in Climate Data. 839-850 - Jingu Kim, Renato D. C. Monteiro, Haesun Park:
Group Sparsity in Nonnegative Matrix Factorization. 851-862 - Ze Tian, Rui Kuang:
Global Linear Neighborhoods for Efficient Label Propagation. 863-872 - Pavel P. Kuksa, Imdadullah Khan, Vladimir Pavlovic:
Generalized Similarity Kernels for Efficient Sequence Classification. 873-882 - Hanbo Dai, Feida Zhu, Ee-Peng Lim, HweeHwa Pang:
Detecting Extreme Rank Anomalous Collections. 883-894 - Yuan Li, Jessica Lin, Tim Oates:
Visualizing Variable-Length Time Series Motifs. 895-906 - Chuanren Liu, Tianming Hu, Yong Ge, Hui Xiong:
Which Distance Metric is Right: An Evolutionary K-Means View. 907-918 - Li-Ping Liu, Xiaoli Z. Fern:
Constructing Training Sets for Outlier Detection. 919-929 - Adam Lugowski, David M. Alber, Aydin Buluç, John R. Gilbert, Steven P. Reinhardt, Yun Teng, Andrew Waranis:
A Flexible Open-Source Toolbox for Scalable Complex Graph Analysis. 930-941 - Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos:
Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection. 942-953 - Pauli Miettinen:
On Finding Joint Subspace Boolean Matrix Factorizations. 954-965 - Marina Sokol, Konstantin Avrachenkov, Paulo Gonçalves, Alexey Mishenin:
Generalized Optimization Framework for Graph-based Semi-supervised Learning. 966-974 - Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
A Tree-Based Kernel for Graphs. 975-986 - Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer Kröger, Hans-Peter Kriegel:
Density-based Projected Clustering over High Dimensional Data Streams. 987-998 - Qiang Zhu, Gustavo E. A. P. A. Batista, Thanawin Rakthanmanon, Eamonn J. Keogh:
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets. 999-1010 - Parikshit Ram, Dongryeol Lee, Alexander G. Gray:
Nearest-Neighbor Search on a Time Budget via Max-Margin Trees. 1011-1022 - Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
Efficient Clustering of Metagenomic Sequences using Locality Sensitive Hashing. 1023-1034 - Nicola Barbieri, Giuseppe Manco, Riccardo Ortale, Ettore Ritacco:
Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data. 1035-1046 - Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel:
On Evaluation of Outlier Rankings and Outlier Scores. 1047-1058 - Sundararajan Sellamanickam, Charu Tiwari, Sathiya Keerthi Selvaraj:
Regularized Structured Output Learning with Partial Labels. 1059-1070 - C. Seshadhri, Ali Pinar, Tamara G. Kolda:
The Similarity Between Stochastic Kronecker and Chung-Lu Graph Models. 1071-1082 - Jiong Yang, Wei Su, Shirong Li, Mehmet M. Dalkiliç:
WIGM: Discovery of Subgraph Patterns in a Large Weighted Graph. 1083-1094 - Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic:
Legislative Prediction via Random Walks over a Heterogeneous Graph. 1095-1106 - Sihong Xie, Wei Fan, Philip S. Yu:
An Iterative and Re-weighting Framework for Rejection and Uncertainty Resolution in Crowdsourcing. 1107-1118 - Xiao Yu, Quanquan Gu, Mianwei Zhou, Jiawei Han:
Citation Prediction in Heterogeneous Bibliographic Networks. 1119-1130 - Peng Wang, Peng Zhang, Li Guo:
Mining Multi-Label Data Streams Using Ensemble-Based Active Learning. 1131-1140 - Charles Zheng, Scott Schwartz, Robert S. Chapkin, Raymond J. Carroll, Ivan Ivanov:
Feature Selection for High-dimensional Integrated Data. 1141-1150
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