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ORCID16th KDD 2010: Washington, DC, USA
- Bharat Rao, Balaji Krishnapuram, Andrew Tomkins, Qiang Yang:
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 H. 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
- Vincent S. Tseng, Cheng-Wei Wu, Bai-En Shie, Philip S. Yu:
UP-Growth: an efficient algorithm for high utility itemset mining. 253-262 - Salvatore Ruggieri:
Frequent regular itemset mining. 263-272 - Liwen Sun, Reynold Cheng, David W. Cheung, Jiefeng Cheng:
Mining uncertain data with probabilistic guarantees. 273-282 - Hoang Thanh Lam, Toon Calders:
Mining top-k frequent items in a data stream with flexible sliding windows. 283-292 - Nikolaj Tatti:
Probably the best itemsets. 293-302
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
- Xin Jin, Mingyang Zhang, Nan Zhang, Gautam Das:
Versatile publishing for privacy preservation. 353-362 - Keng-Pei Lin, Ming-Syan Chen:
Privacy-preserving outsourcing support vector machines with random transformation. 363-372 - Zhen Wen, Ching-Yung Lin:
On the quality of inferring interests from social neighbors. 373-382 - Smruti R. Sarangi, Karin Murthy:
DUST: a generalized notion of similarity between uncertain time series. 383-392 - Vincent Leroy, Berkant Barla Cambazoglu, Francesco Bonchi:
Cold start link prediction. 393-402
Research track 5: classification models and tools
- Xu-Ying Liu, Zhi-Hua Zhou:
Learning with cost intervals. 403-412 - Iris Adä, Michael R. Berthold:
The new iris data: modular data generators. 413-422 - Josh Attenberg, Foster J. Provost:
Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance. 423-432
Research track 6: bioinformatics
- Qiong Fang, Wilfred Ng, Jianlin Feng:
Discovering significant relaxed order-preserving submatrices. 433-442 - Dan He, Douglas Stott Parker Jr.:
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
- Chih-Hua Tai, Philip S. Yu, Ming-Syan Chen:
k-Support anonymity based on pseudo taxonomy for outsourcing of frequent itemset mining. 473-482 - Bin Yang, Hiroshi Nakagawa, Issei Sato, Jun Sakuma:
Collusion-resistant privacy-preserving data mining. 483-492 - Arik Friedman, Assaf Schuster:
Data mining with differential privacy. 493-502 - Raghav Bhaskar, Srivatsan Laxman, Adam D. Smith, Abhradeep Thakurta:
Discovering frequent patterns in sensitive data. 503-512
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 - Mahmud 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 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
- Chi-Hoon Lee:
Learning to combine discriminative classifiers: confidence based. 743-752 - Yuefeng Li, Abdulmohsen Algarni, Ning Zhong:
Mining positive and negative patterns for relevance feature discovery. 753-762 - Guan Yu, Rui-zhang Huang, Zhaojun Wang:
Document clustering via dirichlet process mixture model with feature selection. 763-772 - Frank Reichartz, Hannes Korte, Gerhard Paass:
Semantic relation extraction with kernels over typed dependency trees. 773-782 - Hongning Wang, Yue Lu, Chengxiang Zhai:
Latent aspect rating analysis on review text data: a rating regression approach. 783-792
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 C. 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
- D. Sculley:
Combined regression and ranking. 979-988 - Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, James Swee Chuan Tan:
Mass estimation and its applications. 989-998 - Min-Ling Zhang, Kun Zhang:
Multi-label learning by exploiting label dependency. 999-1008 - Qiaozhu Mei, Jian Guo, Dragomir R. Radev:
DivRank: the interplay of prestige and diversity in information networks. 1009-1018
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 Kabán:
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
- Hillol Kargupta, João Gama, Wei Fan:
The next generation of transportation systems, greenhouse emissions, and data mining. 1209-1212
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