16. KDD 2010:
Washington, DC, USA
Bharat Rao, Balaji Krishnapuram, Andrew Tomkins, Qiang Yang (Eds.):
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, July 25-28, 2010.
ACM 2010, ISBN 978-1-4503-0055-1 
- Qi Lu:
Data mining in the online services industry.
1-2
- Yoav Freund:
Data winnowing.
3-4
- Konrad Feldman:
The quantification of advertising: (+ lessons from building businesses based on large scale data mining).
5-6
IG track 1:
advertising, transportation
- David Chan, Rong Ge, Ori Gershony, Tim Hesterberg, Diane Lambert:
Evaluating online ad campaigns in a pipeline: causal models at scale.
7-16
- Diane Tang, Ashish Agarwal, Deirdre O'Brien, Mike Meyer:
Overlapping experiment infrastructure: more, better, faster experimentation.
17-26
- Wei Li, Xuerui Wang, Ruofei Zhang, Ying Cui, Jianchang Mao, Rong Jin:
Exploitation and exploration in a performance based contextual advertising system.
27-36
- Hillol Kargupta, Kakali Sarkar, Michael Gilligan:
MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system.
37-46
- Santanu Das, Bryan L. Matthews, Ashok N. Srivastava, Nikunj C. Oza:
Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study.
47-56
IG track 2:
business processes
- Saurabh Goorha, Lyle Ungar:
Discovery of significant emerging trends.
57-64
- Mohit Kumar, Rayid Ghani, Zhu-Song Mei:
Data mining to predict and prevent errors in health insurance claims processing.
65-74
- Naoki Abe, Prem Melville, Cezar Pendus, Chandan K. Reddy, David L. Jensen, Vince P. Thomas, James J. Bennett, Gary F. Anderson, Brent R. Cooley, Melissa Kowalczyk, Mark Domick, Timothy Gardinier:
Optimizing debt collections using constrained reinforcement learning.
75-84
- Longbing Cao, Yuming Ou, Philip S. Yu, Gang Wei:
Detecting abnormal coupled sequences and sequence changes in group-based manipulative trading behaviors.
85-94
IG track 3:
software vulnerability, disaster prediction and recovery
- Yanfang Ye, Tao Li, Yong Chen, Qingshan Jiang:
Automatic malware categorization using cluster ensemble.
95-104
- Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker:
Beyond heuristics: learning to classify vulnerabilities and predict exploits.
105-114
- Evan K. Maxwell, Godmar Back, Naren Ramakrishnan:
Diagnosing memory leaks using graph mining on heap dumps.
115-124
- Li Zheng, Chao Shen, Liang Tang, Tao Li, Steven Luis, Shu-Ching Chen, Vagelis Hristidis:
Using data mining techniques to address critical information exchange needs in disaster affected public-private networks.
125-134
- Shen-Shyang Ho, Wenqing Tang, W. Timothy Liu:
Tropical cyclone event sequence similarity search via dimensionality reduction and metric learning.
135-144
IG track 4:
systems and infrastructure, medical
- Collin Bennett, Robert L. Grossman, David Locke, Jonathan Seidman, Steve Vejcik:
Malstone: towards a benchmark for analytics on large data clouds.
145-152
- Furu Wei, Shixia Liu, Yangqiu Song, Shimei Pan, Michelle X. Zhou, Weihong Qian, Lei Shi, Li Tan, Qiang Zhang:
TIARA: a visual exploratory text analytic system.
153-162
- Keith Henderson, Tina Eliassi-Rad, Christos Faloutsos, Leman Akoglu, Lei Li, Koji Maruhashi, B. Aditya Prakash, Hanghang Tong:
Metric forensics: a multi-level approach for mining volatile graphs.
163-172
- Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
Active learning for biomedical citation screening.
173-182
- Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Kuang Chiu, Junling Hu, Honglak Lee:
An integrated machine learning approach to stroke prediction.
183-192
- Yan Yan, Glenn Fung, Jennifer G. Dy, Rómer Rosales:
Medical coding classification by leveraging inter-code relationships.
193-202
Research track 1:
link and click prediction
- Chi Wang, Jiawei Han, Yuntao Jia, Jie Tang, Duo Zhang, Yintao Yu, Jingyi Guo:
Mining advisor-advisee relationships from research publication networks.
203-212
- Deepak Agarwal, Rahul Agrawal, Rajiv Khanna, Nagaraj Kota:
Estimating rates of rare events with multiple hierarchies through scalable log-linear models.
213-222
- Ramakrishnan Srikant, Sugato Basu, Ni Wang, Daryl Pregibon:
User browsing models: relevance versus examination.
223-232
- Maayan Roth, Assaf Ben-David, David Deutscher, Guy Flysher, Ilan Horn, Ari Leichtberg, Naty Leiser, Yossi Matias, Ron Merom:
Suggesting friends using the implicit social graph.
233-242
- Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Chawla:
New perspectives and methods in link prediction.
243-252
Research track 2:
frequent itemsets
Research track 3:
feature selection
- Jun Zhu, Ni Lao, Eric P. Xing:
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields.
303-312
- Liang Sun, Betul Ceran, Jieping Ye:
A scalable two-stage approach for a class of dimensionality reduction techniques.
313-322
- Jun Liu, Lei Yuan, Jieping Ye:
An efficient algorithm for a class of fused lasso problems.
323-332
- Deng Cai, Chiyuan Zhang, Xiaofei He:
Unsupervised feature selection for multi-cluster data.
333-342
- Jian-Bo Yang, Chong Jin Ong:
Feature selection for support vector regression using probabilistic prediction.
343-352
Research track 4:
privacy-sensitive algorithms for learning, publishing, and social networks
Research track 5:
classification models and tools
Research track 6:
bioinformatics
- Qiong Fang, Wilfred Ng, Jianlin Feng:
Discovering significant relaxed order-preserving submatrices.
433-442
- Dan He, D. Stott Parker:
Topic dynamics: an alternative model of bursts in streams of topics.
443-452
- Naren Sundaravaradan, K. S. M. Tozammel Hossain, Vandana Sreedharan, Douglas J. Slotta, John Paul C. Vergara, Lenwood S. Heath, Naren Ramakrishnan:
Extracting temporal signatures for comprehending systems biology models.
453-462
- Jinyan Li, Qian Liu, Tao Zeng:
Negative correlations in collaboration: concepts and algorithms.
463-472
Research track 7:
privacy-sensitive mining
Research track 8:
graph algorithms
- Purnamrita Sarkar, Andrew W. Moore:
Fast nearest-neighbor search in disk-resident graphs.
513-522
- Saeed Alaei, Ravi Kumar, Azarakhsh Malekian, Erik Vee:
Balanced allocation with succinct representation.
523-532
- Hossein Maserrat, Jian Pei:
Neighbor query friendly compression of social networks.
533-542
- Guoming He, Haijun Feng, Cuiping Li, Hong Chen:
Parallel SimRank computation on large graphs with iterative aggregation.
543-552
- Ravi Kumar, Mohammad Mahdian, Mary McGlohon:
Dynamics of conversations.
553-562
Research track 9:
clustering
- Xiang Wang, Ian Davidson:
Flexible constrained spectral clustering.
563-572
- Xuan Hong Dang, James Bailey:
A hierarchical information theoretic technique for the discovery of non linear alternative clusterings.
573-582
- Christian Böhm, Claudia Plant, Junming Shao, Qinli Yang:
Clustering by synchronization.
583-592
- M. Shahriar Hossain, Satish Tadepalli, Layne T. Watson, Ian Davidson, Richard F. Helm, Naren Ramakrishnan:
Unifying dependent clustering and disparate clustering for non-homogeneous data.
593-602
Research track 10:
graph mining and classification
- William B. March, Parikshit Ram, Alexander G. Gray:
Fast euclidean minimum spanning tree: algorithm, analysis, and applications.
603-612
- Jian-Guang Lou, Qiang Fu, Shengqi Yang, Jiang Li, Bin Wu:
Mining program workflow from interleaved traces.
613-622
- Dafna Shahaf, Carlos Guestrin:
Connecting the dots between news articles.
623-632
- Zhaonian Zou, Hong Gao, Jianzhong Li:
Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics.
633-642
- Hongliang Fei, Jun Huan:
Boosting with structure information in the functional space: an application to graph classification.
643-652
Research track 11:
topic modeling
- Seungil Huh, Stephen E. Fienberg:
Discriminative topic modeling based on manifold learning.
653-662
- Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, Naonori Ueda:
Online multiscale dynamic topic models.
663-672
- Issei Sato, Hiroshi Nakagawa:
Topic models with power-law using Pitman-Yor process.
673-682
- Caimei Lu, Xiaohua Hu, Xin Chen, Jung-ran Park, Tingting He, Zhoujun Li:
The topic-perspective model for social tagging systems.
683-692
Research track 12:
algorithms for recommendations
- Michael Jahrer, Andreas Töscher, Robert A. Legenstein:
Combining predictions for accurate recommender systems.
693-702
- Deepak Agarwal, Bee-Chung Chen, Pradheep Elango:
Fast online learning through offline initialization for time-sensitive recommendation.
703-712
- Harald Steck:
Training and testing of recommender systems on data missing not at random.
713-722
- Liang Xiang, Quan Yuan, Shiwan Zhao, Li Chen, Xiatian Zhang, Qing Yang, Jimeng Sun:
Temporal recommendation on graphs via long- and short-term preference fusion.
723-732
- Gengxin Miao, Louise E. Moser, Xifeng Yan, Shu Tao, Yi Chen, Nikos Anerousis:
Generative models for ticket resolution in expert networks.
733-742
Research track 13:
text analysis
Research track 14:
social classification and clustering
- Xiangnan Kong, Philip S. Yu:
Semi-supervised feature selection for graph classification.
793-802
- Christopher DuBois, Padhraic Smyth:
Modeling relational events via latent classes.
803-812
- Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Sun, Jiawei Han:
On community outliers and their efficient detection in information networks.
813-822
- Dan Preston, Carla E. Brodley, Roni Khardon, Damien Sulla-Menashe, Mark A. Friedl:
Redefining class definitions using constraint-based clustering: an application to remote sensing of the earth's surface.
823-832
Research track 15:
classification algorithms and analyses
- Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin:
Large linear classification when data cannot fit in memory.
833-842
- Ryan J. Prenger, Tracy D. Lemmond, Kush R. Varshney, Barry Y. Chen, William G. Hanley:
Class-specific error bounds for ensemble classifiers.
843-852
- Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu:
Designing efficient cascaded classifiers: tradeoff between accuracy and cost.
853-860
- Chuancong Gao, Jianyong Wang:
Direct mining of discriminative patterns for classifying uncertain data.
861-870
- Zhenyu Lu, Xindong Wu, Xingquan Zhu, Josh Bongard:
Ensemble pruning via individual contribution ordering.
871-880
Research track 16:
recommendations:
user models and mobility
- Ni Lao, William W. Cohen:
Fast query execution for retrieval models based on path-constrained random walks.
881-888
- Freddy Chong Tat Chua, Ee-Peng Lim:
Trust network inference for online rating data using generative models.
889-898
- Yong Ge, Hui Xiong, Alexander Tuzhilin, Keli Xiao, Marco Gruteser, Michael J. Pazzani:
An energy-efficient mobile recommender system.
899-908
- Manas Somaiya, Christopher M. Jermaine, Sanjay Ranka:
Mixture models for learning low-dimensional roles in high-dimensional data.
909-918
- Siyuan Liu, Yunhuai Liu, Lionel M. Ni, Jianping Fan, Minglu Li:
Towards mobility-based clustering.
919-928
Research track 17:
social network analysis
- Cindy Xide Lin, Bo Zhao, Qiaozhu Mei, Jiawei Han:
PET: a statistical model for popular events tracking in social communities.
929-938
- Mauro Sozio, Aristides Gionis:
The community-search problem and how to plan a successful cocktail party.
939-948
- Anon Plangprasopchok, Kristina Lerman, Lise Getoor:
Growing a tree in the forest: constructing folksonomies by integrating structured metadata.
949-958
- Dawei Yin, Zhenzhen Xue, Liangjie Hong, Brian D. Davison:
A probabilistic model for personalized tag prediction.
959-968
- Xiaojiang Liu, Zaiqing Nie, Nenghai Yu, Ji-Rong Wen:
BioSnowball: automated population of Wikis.
969-978
Research track 18:
ranking and multi-label learning
Research track 19:
propagation in social networks
- Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Krause:
Inferring networks of diffusion and influence.
1019-1028
- Wei Chen, Chi Wang, Yajun Wang:
Scalable influence maximization for prevalent viral marketing in large-scale social networks.
1029-1038
- Yu Wang, Gao Cong, Guojie Song, Kunqing Xie:
Community-based greedy algorithm for mining top-K influential nodes in mobile social networks.
1039-1048
- Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, Fengjiao Wang:
Social action tracking via noise tolerant time-varying factor graphs.
1049-1058
- Theodoros Lappas, Evimaria Terzi, Dimitrios Gunopulos, Heikki Mannila:
Finding effectors in social networks.
1059-1068
Research track 20:
evolving and spatial data
- Feng Chen, Chang-Tien Lu, Arnold P. Boedihardjo:
GLS-SOD: a generalized local statistical approach for spatial outlier detection.
1069-1078
- Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shixia Liu:
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora.
1079-1088
- Abdullah Mueen, Eamonn J. Keogh:
Online discovery and maintenance of time series motifs.
1089-1098
- Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays, Peter Nye:
Mining periodic behaviors for moving objects.
1099-1108
Research track 21:
KDD methodology
- Zhenxing Wang, Laiwan Chan:
An efficient causal discovery algorithm for linear models.
1109-1118
- Robert J. Durrant, Ata Kaban:
Compressed fisher linear discriminant analysis: classification of randomly projected data.
1119-1128
- Junfeng He, Wei Liu, Shih-Fu Chang:
Scalable similarity search with optimized kernel hashing.
1129-1138
- Wei Liu, Shiqian Ma, Dacheng Tao, Jianzhuang Liu, Peng Liu:
Semi-supervised sparse metric learning using alternating linearization optimization.
1139-1148
- Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian:
Universal multi-dimensional scaling.
1149-1158
Research track 22:
transfer and multi-task learning
- Tianbao Yang, Rong Jin, Anil K. Jain, Yang Zhou, Wei Tong:
Unsupervised transfer classification: application to text categorization.
1159-1168
- Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh:
Nonnegative shared subspace learning and its application to social media retrieval.
1169-1178
- Jianhui Chen, Ji Liu, Jieping Ye:
Learning incoherent sparse and low-rank patterns from multiple tasks.
1179-1188
- Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng:
Multi-task learning for boosting with application to web search ranking.
1189-1198
- Yu Zhang, Dit-Yan Yeung:
Transfer metric learning by learning task relationships.
1199-1208
Panel
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