12. KDD 2006: Philadelphia, PA, USA

Conference invited talks

• John A. Stankovic:
  Self-Organizing wireless sensor networks in action. 1
  
• Andrew Moore:
  New cached-sufficient statistics algorithms for quickly answering statistical questions. 2
  
• Rakesh Agrawal:
  Next frontier. 3
  

Research track papers

• Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
  Deriving quantitative models for correlation clusters. 4-13
  
• Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal:
  Learning to rank networked entities. 14-23
  
• Deepak Agarwal, Andrew McGregor, Jeff M. Phillips, Suresh Venkatasubramanian, Zhengyuan Zhu:
  Spatial scan statistics: approximations and performance study. 24-33
  
• Aris Anagnostopoulos, Michail Vlachos, Marios Hadjieleftheriou, Eamonn J. Keogh, Philip S. Yu:
  Global distance-based segmentation of trajectories. 34-43
  
• Lars Backstrom, Daniel P. Huttenlocher, Jon M. Kleinberg, Xiangyang Lan:
  Group formation in large social networks: membership, growth, and evolution. 44-54
  
• Daniel Barbará, Carlotta Domeniconi, James P. Rogers:
  Detecting outliers using transduction and statistical testing. 55-64
  
• Christian Böhm, Christos Faloutsos, Jia-Yu Pan, Claudia Plant:
  Robust information-theoretic clustering. 65-75
  
• Justin Brickell, Vitaly Shmatikov:
  Efficient anonymity-preserving data collection. 76-85
  
• Gregory Buehrer, Srinivasan Parthasarathy, Amol Ghoting:
  Out-of-core frequent pattern mining on a commodity PC. 86-95
  
• Toon Calders, Bart Goethals, Szymon Jaroszewicz:
  Mining rank-correlated sets of numerical attributes. 96-105
  
• Jin Chen, Wynne Hsu, Mong-Li Lee, See-Kiong Ng:
  NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs. 106-115
  
• Jason V. Davis, Inderjit S. Dhillon:
  Estimating the global pagerank of web communities. 116-125
  
• Chris H. Q. Ding, Tao Li, Wei Peng, Haesun Park:
  Orthogonal nonnegative matrix t-factorizations for clustering. 126-135
  
• Wei Fan, Joe McCloskey, Philip S. Yu:
  A general framework for accurate and fast regression by data summarization in random decision trees. 136-146
  
• Wei Fan, Ian Davidson:
  Reverse testing: an efficient framework to select amongst classifiers under sample selection bias. 147-156
  
• George Forman:
  Quantifying trends accurately despite classifier error and class imbalance. 157-166
  
• Aristides Gionis, Heikki Mannila, Taneli Mielikäinen, Panayiotis Tsaparas:
  Assessing data mining results via swap randomization. 167-176
  
• Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka:
  A new efficient probabilistic model for mining labeled ordered trees. 177-186
  
• Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang:
  Learning the unified kernel machines for classification. 187-196
  
• Tamás Horváth, Jan Ramon, Stefan Wrobel:
  Frequent subgraph mining in outerplanar graphs. 197-206
  
• Alexander T. Ihler, Jon Hutchins, Padhraic Smyth:
  Adaptive event detection with time-varying poisson processes. 207-216
  
• Thorsten Joachims:
  Training linear SVMs in linear time. 217-226
  
• Yiping Ke, James Cheng, Wilfred Ng:
  Mining quantitative correlated patterns using an information-theoretic approach. 227-236
  
• Arno J. Knobbe, Eric K. Y. Ho:
  Maximally informative k-itemsets and their efficient discovery. 237-244
  
• Yehuda Koren, Stephen C. North, Chris Volinsky:
  Measuring and extracting proximity in networks. 245-255
  
• Ravi Kumar, Kunal Punera, Andrew Tomkins:
  Hierarchical topic segmentation of websites. 257-266
  
• Longin Jan Latecki, Marc Sobel, Rolf Lakämper:
  New EM derived from Kullback-Leibler divergence. 267-276
  
• Kristen LeFevre, David J. DeWitt, Raghu Ramakrishnan:
  Workload-aware anonymization. 277-286
  
• Ping Li, Trevor Hastie, Kenneth Ward Church:
  Very sparse random projections. 287-296
  
• Bing Liu, Kaidi Zhao, Jeffrey Benkler, Weimin Xiao:
  Rule interestingness analysis using OLAP operations. 297-306
  
• Elsa Loekito, James Bailey:
  Fast mining of high dimensional expressive contrast patterns using zero-suppressed binary decision diagrams. 307-316
  
• Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip S. Yu:
  Unsupervised learning on k-partite graphs. 317-326
  
• Michael W. Mahoney, Mauro Maggioni, Petros Drineas:
  Tensor-CUR decompositions for tensor-based data. 327-336
  
• Qiaozhu Mei, Dong Xin, Hong Cheng, Jiawei Han, ChengXiang Zhai:
  Generating semantic annotations for frequent patterns with context analysis. 337-346
  
• Taneli Mielikäinen, Evimaria Terzi, Panayiotis Tsaparas:
  Aggregating time partitions. 347-356
  
• Matthew J. Rattigan, Marc Maier, David Jensen:
  Using structure indices for efficient approximation of network properties. 357-366
  
• Rómer Rosales, Glenn Fung:
  Learning sparse metrics via linear programming. 367-373
  
• Jimeng Sun, Dacheng Tao, Christos Faloutsos:
  Beyond streams and graphs: dynamic tensor analysis. 374-383
  
• Lei Tang, Jianping Zhang, Huan Liu:
  Acclimatizing taxonomic semantics for hierarchical content classification from semantics to data-driven taxonomy. 384-393
  
• Yufei Tao, Xiaokui Xiao, Shuigeng Zhou:
  Mining distance-based outliers from large databases in any metric space. 394-403
  
• Hanghang Tong, Christos Faloutsos:
  Center-piece subgraphs: problem definition and fast solutions. 404-413
  
• Ke Wang, Benjamin C. M. Fung:
  Anonymizing sequential releases. 414-423
  
• Xuerui Wang, Andrew McCallum:
  Topics over time: a non-Markov continuous-time model of topical trends. 424-433
  
• Geoffrey I. Webb:
  Discovering significant rules. 434-443
  
• Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han:
  Extracting redundancy-aware top-k patterns. 444-453
  
• Jieping Ye, Tie Wang:
  Regularized discriminant analysis for high dimensional, low sample size data. 454-463
  
• Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel, Mingrui Wu:
  Supervised probabilistic principal component analysis. 464-473
  
• Dell Zhang, Wee Sun Lee:
  Extracting key-substring-group features for text classification. 474-483
  
• Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei-Ying Ma:
  Event detection from evolution of click-through data. 484-493
  
• Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Ying Ma:
  Simultaneous record detection and attribute labeling in web data extraction. 494-503
  

Research track posters

• Naoki Abe, Bianca Zadrozny, John Langford:
  Outlier detection by active learning. 504-509
  
• Charu C. Aggarwal, Jian Pei, Bo Zhang:
  On privacy preservation against adversarial data mining. 510-516
  
• Bavani Arunasalam, Sanjay Chawla:
  CCCS: a top-down associative classifier for imbalanced class distribution. 517-522
  
• Tanya Y. Berger-Wolf, Jared Saia:
  A framework for analysis of dynamic social networks. 523-528
  
• Indrajit Bhattacharya, Lise Getoor, Louis Licamele:
  Query-time entity resolution. 529-534
  
• Cristian Bucila, Rich Caruana, Alexandru Niculescu-Mizil:
  Model compression. 535-541
  
• Robin D. Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik:
  Classification features for attack detection in collaborative recommender systems. 542-547
  
• Vitor R. Carvalho, William W. Cohen:
  Single-pass online learning: performance, voting schemes and online feature selection. 548-553
  
• Deepayan Chakrabarti, Ravi Kumar, Andrew Tomkins:
  Evolutionary clustering. 554-560
  
• Aristides Gionis, Heikki Mannila, Kai Puolamäki, Antti Ukkonen:
  Algorithms for discovering bucket orders from data. 561-566
  
• Hongyu Guo, Herna L. Viktor:
  Mining relational data through correlation-based multiple view validation. 567-573
  
• Tomoharu Iwata, Kazumi Saito, Takeshi Yamada:
  Recommendation method for extending subscription periods. 574-579
  
• Wolfgang Jank, Galit Shmueli, Shanshan Wang:
  Dynamic, real-time forecasting of online auctions via functional models. 580-585
  
• Szymon Jaroszewicz:
  Polynomial association rules with applications to logistic regression. 586-591
  
• Nan Jiang, Le Gruenwald:
  CFI-Stream: mining closed frequent itemsets in data streams. 592-597
  
• Arnd Christian König, Eric Brill:
  Reducing the human overhead in text categorization. 598-603
  
• Deept Kumar, Naren Ramakrishnan, Richard F. Helm, Malcolm Potts:
  Algorithms for storytelling. 604-610
  
• Ravi Kumar, Jasmine Novak, Andrew Tomkins:
  Structure and evolution of online social networks. 611-617
  
• Sven Laur, Helger Lipmaa, Taneli Mielikäinen:
  Cryptographically private support vector machines. 618-624
  
• Hady Wirawan Lauw, Ee-Peng Lim, Ke Wang:
  Bias and controversy: beyond the statistical deviation. 625-630
  
• Jure Leskovec, Christos Faloutsos:
  Sampling from large graphs. 631-636
  
• Jinze Liu, Qi Zhang, Wei Wang, Leonard McMillan, Jan Prins:
  Clustering pair-wise dissimilarity data into partially ordered sets. 637-642
  
• Dharmesh M. Maniyar, Ian T. Nabney:
  Visual data mining using principled projection algorithms and information visualization techniques. 643-648
  
• Qiaozhu Mei, ChengXiang Zhai:
  A mixture model for contextual text mining. 649-655
  
• Srujana Merugu, Saharon Rosset, Claudia Perlich:
  A new multi-view regression approach with an application to customer wallet estimation. 656-661
  
• Riadh Ben Messaoud, Omar Boussaid, Sabine Loudcher Rabaséda:
  Efficient multidimensional data representations based on multiple correspondence analysis. 662-667
  
• Fabian Mörchen:
  Algorithms for time series knowledge mining. 668-673
  
• J. Saketha Nath, Chiranjib Bhattacharyya, M. Narasimha Murty:
  Clustering based large margin classification: a scalable approach using SOCP formulation. 674-679
  
• David Newman, Chaitanya Chemudugunta, Padhraic Smyth:
  Statistical entity-topic models. 680-686
  
• Noam Palatin, Arie Leizarowitz, Assaf Schuster, Ran Wolff:
  Mining for misconfigured machines in grid systems. 687-692
  
• Jia-Yu Pan, André G. R. Balan, Eric P. Xing, Agma J. M. Traina, Christos Faloutsos:
  Automatic mining of fruit fly embryo images. 693-698
  
• Seung-Taek Park, David Pennock, Omid Madani, Nathan Good, Dennis DeCoste:
  Naïve filterbots for robust cold-start recommendations. 699-705
  
• Myra Spiliopoulou, Irene Ntoutsi, Yannis Theodoridis, Rene Schult:
  MONIC: modeling and monitoring cluster transitions. 706-711
  
• Fabian M. Suchanek, Georgiana Ifrim, Gerhard Weikum:
  Combining linguistic and statistical analysis to extract relations from web documents. 712-717
  
• Bin Tan, Xuehua Shen, ChengXiang Zhai:
  Mining long-term search history to improve search accuracy. 718-723
  
• Ivor W. Tsang, András Kocsor, James T. Kwok:
  Efficient kernel feature extraction for massive data sets. 724-729
  
• Chao Wang, Srinivasan Parthasarathy:
  Summarizing itemset patterns using probabilistic models. 730-735
  
• Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jeffrey Xu Yu:
  Suppressing model overfitting in mining concept-drifting data streams. 736-741
  
• Steve Wedig, Omid Madani:
  A large-scale analysis of query logs for assessing personalization opportunities. 742-747
  
• Li Wei, Eamonn J. Keogh:
  Semi-supervised time series classification. 748-753
  
• Raymond Chi-Wing Wong, Jiuyong Li, Ada Wai-Chee Fu, Ke Wang:
  (alpha, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing. 754-759
  
• Gang Wu, Edward Y. Chang, Yen-Kuang Chen, Christoper Hughes:
  Incremental approximate matrix factorization for speeding up support vector machines. 760-766
  
• Mingxi Wu, Chris Jermaine:
  Outlier detection by sampling with accuracy guarantees. 767-772
  
• Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han:
  Discovering interesting patterns through user's interactive feedback. 773-778
  
• Hui Xiong, Junjie Wu, Jian Chen:
  K-means clustering versus validation measures: a data distribution perspective. 779-784
  
• Jian Xu, Wei Wang, Jian Pei, Xiaoyuan Wang, Baile Shi, Ada Wai-Chee Fu:
  Utility-based anonymization using local recoding. 785-790
  
• Illhoi Yoo, Xiaohua Hu, Il-Yeol Song:
  Integration of semantic-based bipartite graph representation and mutual refinement strategy for biomedical literature clustering. 791-796
  
• Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Karypis:
  Coherent closed quasi-clique discovery from large dense graph databases. 797-802
  
• Minghua Zhang, Wynne Hsu, Mong-Li Lee:
  Mining progressive confident rules. 803-808
  
• Sheng Zhang, Amit Chakrabarti, James Ford, Fillia Makedon:
  Attack detection in time series for recommender systems. 809-814
  
• Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhang:
  Identifying bridging rules between conceptual clusters. 815-820
  
• Tong Zhang, Alexandrin Popescul, Byron Dom:
  Linear prediction models with graph regularization for web-page categorization. 821-826
  
• Lizhuang Zhao, Mohammed J. Zaki, Naren Ramakrishnan:
  BLOSOM: a framework for mining arbitrary boolean expressions. 827-832
  

Industrial and government applications track invited talks

• Jeff Jonas:
  Introducing perpetual analytics. 833
  
• William Kahn:
  Capital One's statistical problems: our top ten list. 834
  
• Andrew McCallum:
  Information extraction, data mining and joint inference. 835
  
• Michael Cavaretta:
  Data mining challenges in the automotive domain. 836
  

Industrial and government applications track papers

• Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Toshiro Kubota, Glenn Fung, Marcos Salganicoff, R. Bharat Rao:
  Computer aided detection via asymmetric cascade of sparse hyperplane classifiers. 837-844
  
• Rebecca Castaño, Dominic Mazzoni, Nghia Tang, Ronald Greeley, Thomas Doggett, Benjamin Cichy, Steve A. Chien, Ashley Davies:
  Onboard classifiers for science event detection on a remote sensing spacecraft. 845-851
  
• George Forman, Evan Kirshenbaum, Jaap Suermondt:
  Pragmatic text mining: minimizing human effort to quantify many issues in call logs. 852-861
  
• Seth Hettich, Michael J. Pazzani:
  Mining for proposal reviewers: lessons learned at the national science foundation. 862-871
  
• Chao Liu, Chen Chen, Jiawei Han, Philip S. Yu:
  GPLAG: detection of software plagiarism by program dependence graph analysis. 872-881
  
• Fabian Mörchen, Ingo Mierswa, Alfred Ultsch:
  Understandable models Of music collections based on exhaustive feature generation with temporal statistics. 882-891
  
• Kaidi Zhao, Bing Liu, Jeffrey Benkler, Weimin Xiao:
  Opportunity map: identifying causes of failure - a deployed data mining system. 892-901
  

Industrial and government applications track posters

• Eugene Agichtein, Zijian Zheng:
  Identifying "best bet" web search results by mining past user behavior. 902-908
  
• Rich Caruana, Mohamed Farid Elhawary, Art Munson, Mirek Riedewald, Daria Sorokina, Daniel Fink, Wesley M. Hochachka, Steve Kelling:
  Mining citizen science data to predict orevalence of wild bird species. 909-915
  
• Julien Etienne, Bernd Wachmann, Lei Zhang:
  A component-based framework for knowledge discovery in bioinformatics. 916-921
  
• Byron J. Gao, Obi L. Griffith, Martin Ester, Steven J. M. Jones:
  Discovering significant OPSM subspace clusters in massive gene expression data. 922-928
  
• Charles X. Ling, Victor S. Sheng, Tilmann F. W. Bruckhaus, Nazim H. Madhavji:
  Maximum profit mining and its application in software development. 929-934
  
• Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Martin Scholz, Timm Euler:
  YALE: rapid prototyping for complex data mining tasks. 935-940
  
• Sankar Virdhagriswaran, Gordon Dakin:
  Camouflaged fraud detection in domains with complex relationships. 941-947
  
• Lian Yan, Patrick Baldasare:
  Beyond classification and ranking: constrained optimization of the ROI. 948-953
  

Panel

• Gregory Piatetsky-Shapiro, Robert Grossman, Chabane Djeraba, Ronen Feldman, Lise Getoor, Mohammed Javeed Zaki:
  Is there a grand challenge or X-prize for data mining? 954-956