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ORCID10th SDM 2010: Columbus, Ohio, USA
- Proceedings of the SIAM International Conference on Data Mining, SDM 2010, April 29 - May 1, 2010, Columbus, Ohio, USA. SIAM 2010, ISBN 978-0-89871-703-7
Session S1: Text Mining
- Syed Fawad Hussain
, Gilles Bisson:
Text Categorization Using Word Similarities Based on Higher Order Co-occurrences. 1-12 - Fuzhen Zhuang, Ping Luo, Hui Xiong, Qing He, Yuhong Xiong, Zhongzhi Shi:
Exploiting Associations between Word Clusters and Document Classes for Cross-Domain Text Categorization. 13-24 - Pavel P. Kuksa, Yanjun Qi:
Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning. 25-36 - Muhammad Asiful Islam, Faisal Ahmed, Yevgen Borodin, Jalal Mahmud, I. V. Ramakrishnan:
Improving Accessibility of Transaction-centric Web Objects. 37-48
Session S2: Privacy and Trust
- Niko Vuokko, Evimaria Terzi:
Reconstructing Randomized Social Networks. 49-59 - Leting Wu, Xiaowei Ying, Xintao Wu:
Reconstruction from Randomized Graph via Low Rank Approximation. 60-71 - Viet-An Nguyen, Ee-Peng Lim, Hwee-Hoon Tan, Jing Jiang, Aixin Sun:
Do You Trust to Get Trust? A Study of Trust Reciprocity Behaviors and Reciprocal Trust Prediction. 72-83 - Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Raymond Chi-Wing Wong:
Publishing Skewed Sensitive Microdata. 84-93
Session S3: Clustering
- Ian Davidson, S. S. Ravi, Leonid Shamis:
A SAT-based Framework for Efficient Constrained Clustering. 94-105 - Wen-Yun Yang, James T. Kwok, Bao-Liang Lu:
Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm. 106-117 - Xuan-Hong Dang, James Bailey:
Generation of Alternative Clusterings Using the CAMI Approach. 118-129 - Greg Hamerly:
Making k-means Even Faster. 130-140
Session S4: Pattern Mining
- Pritam Chanda, Jianmei Yang, Aidong Zhang, Murali Ramanathan:
On Mining Statistically Significant Attribute Association Information. 141-152 - Kleanthis-Nikolaos Kontonasios, Tijl De Bie:
An Information-Theoretic Approach to Finding Informative Noisy Tiles in Binary Databases. 153-164 - Claudio Lucchese, Salvatore Orlando, Raffaele Perego:
Mining Top-K Patterns from Binary Datasets in Presence of Noise. 165-176 - Mario Boley, Thomas Gärtner, Henrik Grosskreutz:
Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining. 177-188
Session S5: Recommendation
- Beau Piccart, Jan Struyf, Hendrik Blockeel:
Alleviating the Sparsity Problem in Collaborative Filtering by Using an Adapted Distance and a Graph-Based Method. 189-198 - Quanquan Gu, Jie Zhou, Chris H. Q. Ding:
Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs. 199-210 - Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell:
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization. 211-222 - Hanhuai Shan, Arindam Banerjee:
Residual Bayesian Co-clustering for Matrix Approximation. 223-234
Session S6: Support Vector Machines
- Guangxia Li, Steven C. H. Hoi, Kuiyu Chang:
Two-View Transductive Support Vector Machines. 235-244 - Hua Ouyang, Alexander G. Gray:
Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs. 245-256 - Stefano Lodi, Ricardo Ñanculef, Claudio Sartori:
Single-Pass Distributed Learning of Multi-class SVMs Using Core-Sets. 257-268 - Xiaoxu Han:
Nonnegative Principal Component Analysis for Proteomic Tumor Profiles. 269-280
Session S7: Supervised Learning
- Fei Wang, Ping Li:
Efficient Nonnegative Matrix Factorization with Random Projections. 281-292 - Tao Li, Vikas Sindhwani, Chris H. Q. Ding, Yi Zhang:
Bridging Domains with Words: Opinion Analysis with Matrix Tri-factorizations. 293-302 - Shin Matsushima, Nobuyuki Shimizu, Kazuhiro Yoshida, Takashi Ninomiya, Hiroshi Nakagawa:
Exact Passive-Aggressive Algorithm for Multiclass Classification Using Support Class. 303-314
Session S8: Spatial-Temporal Pattern Mining
- Fabian Mörchen, Dmitriy Fradkin:
Robust Mining of Time Intervals with Semi-interval Partial Order Patterns. 315-326 - Pradeep Mohan, Shashi Shekhar, James A. Shine, James P. Rogers:
Cascading Spatio-temporal Pattern Discovery: A Summary of Results. 327-338 - Shin-ichi Minato, Takeaki Uno:
Frequentness-Transition Queries for Distinctive Pattern Mining from Time-Segmented Databases. 339-349 - Niko Vuokko:
Consecutive Ones Property and Spectral Ordering. 350-360
Session S9: Uncertainty in Data Mining
- Jiazhen He, Yang Zhang, Xue Li, Yong Wang:
Naive Bayes Classifier for Positive Unlabeled Learning with Uncertainty. 361-372 - Charu C. Aggarwal:
On Multidimensional Sharpening of Uncertain Data. 373-384 - Stephan Günnemann, Hardy Kremer, Thomas Seidl:
Subspace Clustering for Uncertain Data. 385-396 - Daan Fierens:
On the Use of Combining Rules in Relational Probability Trees. 397-408
Session S10: Clustering and Outlier Detection
- Brian Delaney, Andrew S. Fast, William M. Campbell, Clifford J. Weinstein, David D. Jensen:
The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity. 409-417 - Yu-Ru Lin, Jimeng Sun, Nan Cao, Shixia Liu:
ContexTour: Contextual Contour Analysis on Dynamic Multi-relational Clustering. 418-429 - Ou Wu, Jun Gao, Weiming Hu, Bing Li, Mingliang Zhu:
Identifying Multi-instance Outliers. 430-441 - Kelvin Sim, Ardian Kristanto Poernomo, Vivekanand Gopalkrishnan:
Mining Actionable Subspace Clusters in Sequential Data. 442-453
Session S11: Graph Mining
- Kristen LeFevre, Evimaria Terzi:
GraSS: Graph Structure Summarization. 454-465 - Akihiro Inokuchi, Takashi Washio:
Mining Frequent Graph Sequence Patterns Induced by Vertices. 466-477 - Charu C. Aggarwal, Yuchen Zhao, Philip S. Yu:
On Clustering Graph Streams. 478-489 - Sourav Mukherjee, Tim Oates:
Inferring Probability Distributions of Graph Size and Node Degree from Stochastic Graph Grammars. 490-501
Session S12: Feature Learning and Prediction
- Jaegul Choo, Chandan K. Reddy, Hanseung Lee, Haesun Park:
p-ISOMAP: An Efficient Parametric Update for ISOMAP for Visual Analytics. 502-513 - Marie desJardins, James MacGlashan, Kiri L. Wagstaff:
Confidence-Based Feature Acquisition to Minimize Training and Test Costs. 514-524 - Jingrui He, Jaime G. Carbonell:
Co-selection of Features and Instances for Unsupervised Rare Category Analysis. 525-536 - Abhimanyu Lad, Yiming Yang:
Active Ordering of Interactive Prediction Tasks. 537-547 - U Kang, Charalampos E. Tsourakakis, Ana Paula Appel, Christos Faloutsos, Jure Leskovec:
Radius Plots for Mining Tera-byte Scale Graphs: Algorithms, Patterns, and Observations. 548-558
Session S13: Mining Large Graphs
- Jérôme Kunegis, Stephan Schmidt, Andreas Lommatzsch, Jürgen Lerner, Ernesto William De Luca, Sahin Albayrak:
Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization. 559-570 - Pei Li, Hongyan Liu, Jeffrey Xu Yu, Jun He, Xiaoyong Du:
Fast Single-Pair SimRank Computation. 571-582 - TaeHyun Hwang, Rui Kuang:
A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery. 583-594 - Masashi Sugiyama, Satoshi Hara, Paul von Bünau, Taiji Suzuki, Takafumi Kanamori, Motoaki Kawanabe:
Direct Density Ratio Estimation with Dimensionality Reduction. 595-606
Session S14: Feature Selection
- Charu C. Aggarwal:
The Generalized Dimensionality Reduction Problem. 607-618 - Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, Jennifer G. Dy:
Convex Principal Feature Selection. 619-628 - Wei Fan, Erheng Zhong, Jing Peng, Olivier Verscheure, Kun Zhang, Jiangtao Ren, Rong Yan, Qiang Yang:
Generalized and Heuristic-Free Feature Construction for Improved Accuracy. 629-640
Session S15: Time Series
- Alireza Vahdatpour, Majid Sarrafzadeh:
Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems. 641-652 - Zubin Abraham, Pang-Ning Tan:
An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data. 653-664 - Nuno Filipe Castro, Paulo J. Azevedo:
Multiresolution Motif Discovery in Time Series. 665-676 - Milos Radovanovic, Alexandros Nanopoulos, Mirjana Ivanovic:
Time-Series Classification in Many Intrinsic Dimensions. 677-688
Session S16: Tensors
- Charalampos E. Tsourakakis:
MACH: Fast Randomized Tensor Decompositions. 689-700 - Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Morten Mørup:
Scalable Tensor Factorizations with Missing Data. 701-712 - Michael J. O'Hara:
On Low-Rank Updates to the Singular Value and Tucker Decompositions. 713-719
Session S17: Social Network Mining
- Zhen Wen, Ching-Yung Lin:
Towards Finding Valuable Topics. 720-731 - Yossi Richter, Elad Yom-Tov, Noam Slonim:
Predicting Customer Churn in Mobile Networks through Analysis of Social Groups. 732-741 - Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin:
Directed Network Community Detection: A Popularity and Productivity Link Model. 742-753 - Keith Henderson, Tina Eliassi-Rad, Spiros Papadimitriou, Christos Faloutsos:
HCDF: A Hybrid Community Discovery Framework. 754-765
Session S18: Classification
- Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V. Chawla:
A Robust Decision Tree Algorithm for Imbalanced Data Sets. 766-777 - Xiatian Zhang, Quan Yuan, Shiwan Zhao, Wei Fan, Wentao Zheng, Zhong Wang:
Multi-label Classification without the Multi-label Cost. 778-789 - Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nansheng Chen:
Fast and Accurate Gene Prediction by Decision Tree Classification. 790-801 - Charu C. Aggarwal, Philip S. Yu:
On Classification of High-Cardinality Data Streams. 802-813
Session S19: Classification and Applications
- Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip S. Yu:
Predictive Modeling with Heterogeneous Sources. 814-825 - Pinar Donmez, Jaime G. Carbonell, Jeff G. Schneider:
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy. 826-837 - Zheng Zhao, Jiangxin Wang, Shashvata Sharma, Nitin Agarwal, Huan Liu, Yung Chang:
An Integrative Approach to Indentifying Biologically Relevant Genes. 838-849 - Bilson J. L. Campana, Eamonn J. Keogh:
A Compression Based Distance Measure for Texture. 850-861
Session S20: Machine Learning
- Yunpeng Cai, Yijun Sun, Yubo Cheng, Jian Li, Steve Goodison:
Fast Implementation of ℓ1Regularized Learning Algorithms Using Gradient Descent Methods. 862-871 - Yi Zhang, Jeff G. Schneider, Artur Dubrawski:
Learning Compressible Models. 872-881 - Malik Magdon-Ismail, Konstantin Mertsalov:
A Permutation Approach to Validation. 882-893 - Zhenyu Lu, Xindong Wu, Josh C. Bongard:
Adaptive Informative Sampling for Active Learning. 894-905
Session S21: Potpourri
- Markus Ojala, Gemma C. Garriga, Aristides Gionis, Heikki Mannila:
Evaluating Query Result Significance in Databases via Randomizations. 906-917 - Nan Li, Yinghui Yang, Xifeng Yan:
Cross-Selling Optimization for Customized Promotion. 918-929 - Nitin Jindal, Bing Liu:
A Generalized Tree Matching Algorithm Considering Nested Lists for Web Data Extraction. 930-941 - Faris Alqadah, Raj Bhatnagar, Anil G. Jegga:
Mining Maximally Banded Matrices in Binary Data. 942-953
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