10. KDD 2004: Seattle, WA, USA

@proceedings{DBLP:conf/kdd/2004,
  editor    = {Won Kim and
               Ron Kohavi and
               Johannes Gehrke and
               William DuMouchel},
  title     = {Proceedings of the Tenth ACM SIGKDD International Conference
               on Knowledge Discovery and Data Mining, Seattle, Washington,
               USA, August 22-25, 2004},
  booktitle = {KDD},
  publisher = {ACM},
  year      = {2004},
  isbn      = {1-58113-888-1},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

• Eric Haseltine:
  User-centered design for KDD. 1
  
• David Heckerman:
  Graphical models for data mining. 2
  

Research track papers

• Naoki Abe, Bianca Zadrozny, John Langford:
  An iterative method for multi-class cost-sensitive learning. 3-11
  
• Foto N. Afrati, Aristides Gionis, Heikki Mannila:
  Approximating a collection of frequent sets. 12-19
  
• Eugene Agichtein, Venkatesh Ganti:
  Mining reference tables for automatic text segmentation. 20-29
  
• Edoardo Airoldi, Christos Faloutsos:
  Recovering latent time-series from their observed sums: network tomography with particle filters. 30-39
  
• Brigham Anderson, Andrew W. Moore, Andrew Connolly, Robert Nichol:
  Fast nonlinear regression via eigenimages applied to galactic morphology. 40-48
  
• Anthony J. Bagnall, Gareth J. Janacek:
  Clustering time series from ARMA models with clipped data. 49-58
  
• Sugato Basu, Mikhail Bilenko, Raymond J. Mooney:
  A probabilistic framework for semi-supervised clustering. 59-68
  
• Rich Caruana, Alexandru Niculescu-Mizil:
  Data mining in metric space: an empirical analysis of supervised learning performance criteria. 69-78
  
• Deepayan Chakrabarti, Spiros Papadimitriou, Dharmendra S. Modha, Christos Faloutsos:
  Fully automatic cross-associations. 79-88
  
• William W. Cohen, Sunita Sarawagi:
  Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods. 89-98
  
• Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. Sanghai, Deepak Verma:
  Adversarial classification. 99-108
  
• Theodoros Evgeniou, Massimiliano Pontil:
  Regularized multi--task learning. 109-117
  
• Christos Faloutsos, Kevin S. McCurley, Andrew Tomkins:
  Fast discovery of connection subgraphs. 118-127
  
• Wei Fan:
  Systematic data selection to mine concept-drifting data streams. 128-137
  
• Krishna Gade, Jianyong Wang, George Karypis:
  Efficient closed pattern mining in the presence of tough block constraints. 138-147
  
• Bin He, Kevin Chen-Chuan Chang, Jiawei Han:
  Discovering complex matchings across web query interfaces: a correlation mining approach. 148-157
  
• Tamás Horváth, Thomas Gärtner, Stefan Wrobel:
  Cyclic pattern kernels for predictive graph mining. 158-167
  
• Minqing Hu, Bing Liu:
  Mining and summarizing customer reviews. 168-177
  
• Szymon Jaroszewicz, Dan A. Simovici:
  Interestingness of frequent itemsets using Bayesian networks as background knowledge. 178-186
  
• Glen Jeh, Jennifer Widom:
  Mining the space of graph properties. 187-196
  
• Xin Jin, Yanzan Zhou, Bamshad Mobasher:
  Web usage mining based on probabilistic latent semantic analysis. 197-205
  
• Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) Ratanamahatana:
  Towards parameter-free data mining. 206-215
  
• Ravi Kumar, Uma Mahadevan, D. Sivakumar:
  A graph-theoretic approach to extract storylines from search results. 216-225
  
• Cuiping Li, Gao Cong, Anthony K. H. Tung, Shan Wang:
  Incremental maintenance of quotient cube for median. 226-235
  
• Nikos Mamoulis, Huiping Cao, George Kollios, Marios Hadjieleftheriou, Yufei Tao, David W. Cheung:
  Mining, indexing, and querying historical spatiotemporal data. 236-245
  
• Ion Muslea:
  Machine learning for online query relaxation. 246-255
  
• Daniel B. Neill, Andrew W. Moore:
  Rapid detection of significant spatial clusters. 256-265
  
• Naren Ramakrishnan, Deept Kumar, Bud Mishra, Malcolm Potts, Richard F. Helm:
  Turning CARTwheels: an alternating algorithm for mining redescriptions. 266-275
  
• Jude W. Shavlik, Mark Shavlik:
  Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. 276-285
  
• Andrew T. Smith, Charles Elkan:
  A Bayesian network framework for reject inference. 286-295
  
• Michael Steinbach, Pang-Ning Tan, Vipin Kumar:
  Support envelopes: a technique for exploring the structure of association patterns. 296-305
  
• Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, Thomas L. Griffiths:
  Probabilistic author-topic models for information discovery. 306-315
  
• Chen Wang, Wei Wang, Jian Pei, Yongtai Zhu, Baile Shi:
  Scalable mining of large disk-based graph databases. 316-325
  
• Xiaoyun Wu, Rohini K. Srihari:
  Incorporating prior knowledge with weighted margin support vector machines. 326-333
  
• Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar:
  Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs. 334-343
  
• Guizhen Yang:
  The complexity of mining maximal frequent itemsets and maximal frequent patterns. 344-353
  
• Jieping Ye, Ravi Janardan, Qi Li:
  GPCA: an efficient dimension reduction scheme for image compression and retrieval. 354-363
  
• Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, Vipin Kumar:
  IDR/QR: an incremental dimension reduction algorithm via QR decomposition. 364-373
  
• Hong Zhang, Balaji Padmanabhan, Alexander Tuzhilin:
  On the discovery of significant statistical quantitative rules. 374-383
  
• Xin Zhang, Nikos Mamoulis, David W. Cheung, Yutao Shou:
  Fast mining of spatial collocations. 384-393
  

Industry/government track papers

• Kamal Ali, Wijnand van Stam:
  TiVo: making show recommendations using a distributed collaborative filtering architecture. 394-401
  
• Chad M. Cumby, Andrew E. Fano, Rayid Ghani, Marko Krema:
  Predicting customer shopping lists from point-of-sale purchase data. 402-409
  
• Lin Deng, Jian Pei, Jinwen Ma, Dik Lun Lee:
  A rank sum test method for informative gene discovery. 410-419
  
• Steve Donoho:
  Early detection of insider trading in option markets. 420-429
  
• Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tang, Aidong Zhang:
  Mining coherent gene clusters from gene-sample-time microarray data. 430-439
  
• Tsuyoshi Idé, Hisashi Kashima:
  Eigenspace-based anomaly detection in computer systems. 440-449
  
• Aleksandar Lazarevic, Ramdev Kanapady, Chandrika Kamath:
  Effective localized regression for damage detection in large complex mechanical structures. 450-459
  
• Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jeffrey P. Lankford, Donna M. Nystrom:
  Visually mining and monitoring massive time series. 460-469
  
• Jeremy Z. Kolter, Marcus A. Maloof:
  Learning to detect malicious executables in the wild. 470-478
  
• Lian Yan, David Verbel, Olivier Saidi:
  Predicting prostate cancer recurrence via maximizing the concordance index. 479-485
  
• Kenichi Yoshida, Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Nakashima, Hiromitsu Fujikawa, Katsuyuki Yamazaki:
  Density-based spam detector. 486-493
  
• Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Schaller:
  V-Miner: using enhanced parallel coordinates to mine product design and test data. 494-502
  

Research track posters

• Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
  On demand classification of data streams. 503-508
  
• Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha:
  A generalized maximum entropy approach to bregman co-clustering and matrix approximation. 509-514
  
• Arindam Banerjee, John Langford:
  An objective evaluation criterion for clustering. 515-520
  
• Jinbo Bi, Tong Zhang, Kristin P. Bennett:
  Column-generation boosting methods for mixture of kernels. 521-526
  
• Hong Cheng, Xifeng Yan, Jiawei Han:
  IncSpan: incremental mining of sequential patterns in large database. 527-532
  
• James Chilson, Raymond T. Ng, Alan Wagner, Ruben H. Zamar:
  Parallel computation of high dimensional robust correlation and covariance matrices. 533-538
  
• Kaustav Das, Andrew W. Moore, Jeff G. Schneider:
  Belief state approaches to signaling alarms in surveillance systems. 539-544
  
• Ian Davidson, Goutam Paul:
  Locating secret messages in images. 545-550
  
• Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis:
  Kernel k-means: spectral clustering and normalized cuts. 551-556
  
• Martin Ester, Rong Ge, Wen Jin, Zengjian Hu:
  A microeconomic data mining problem: customer-oriented catalog segmentation. 557-562
  
• Bobi Gilburd, Assaf Schuster, Ran Wolff:
  k-TTP: a new privacy model for large-scale distributed environments. 563-568
  
• Giles Hooker:
  Diagnosing extrapolation: tree-based density estimation. 569-574
  
• Giles Hooker:
  Discovering additive structure in black box functions. 575-580
  
• Jun Huan, Wei Wang, Jan Prins, Jiong Yang:
  SPIN: mining maximal frequent subgraphs from graph databases. 581-586
  
• Vijay S. Iyengar:
  On detecting space-time clusters. 587-592
  
• David Jensen, Jennifer Neville, Brian Gallagher:
  Why collective inference improves relational classification. 593-598
  
• Murat Kantarcioglu, Jiashun Jin, Chris Clifton:
  When do data mining results violate privacy? 599-604
  
• Aleksander Kolcz, Abdur Chowdhury, Joshua Alspector:
  Improved robustness of signature-based near-replica detection via lexicon randomization. 605-610
  
• Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agrawal:
  Learning spatially variant dissimilarity (SVaD) measures. 611-616
  
• Yifan Li, Jiawei Han, Jiong Yang:
  Clustering moving objects. 617-622
  
• Jinze Liu, Wei Wang, Jiong Yang:
  A framework for ontology-driven subspace clustering. 623-628
  
• Ting Liu, Ke Yang, Andrew W. Moore:
  The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data. 629-634
  
• Avraham A. Melkman, Eran Shaham:
  Sleeved coclustering. 635-640
  
• Apostol Natsev, Milind R. Naphade, John R. Smith:
  Semantic representation: search and mining of multimedia content. 641-646
  
• Siegfried Nijssen, Joost N. Kok:
  A quickstart in frequent structure mining can make a difference. 647-652
  
• Jia-Yu Pan, Hyung-Jeong Yang, Christos Faloutsos, Pinar Duygulu:
  Automatic multimedia cross-modal correlation discovery. 653-658
  
• David Poole:
  Estimating the size of the telephone universe: a Bayesian Mark-recapture approach. 659-664
  
• Alexandrin Popescul, Lyle H. Ungar:
  Cluster-based concept invention for statistical relational learning. 665-670
  
• Paat Rusmevichientong, Shenghuo Zhu, David Selinger:
  Identifying early buyers from purchase data. 671-677
  
• Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerome P. Reiter:
  Privacy preserving regression modelling via distributed computation. 677-682
  
• Jouni K. Seppänen, Heikki Mannila:
  Dense itemsets. 683-688
  
• Michael Steinbach, Pang-Ning Tan, Hui Xiong, Vipin Kumar:
  Generalizing the notion of support. 689-694
  
• Pang-Ning Tan, Rong Jin:
  Ordering patterns by combining opinions from multiple sources. 695-700
  
• Peter Tiño, Ata Kabán, Yi Sun:
  A generative probabilistic approach to visualizing sets of symbolic sequences. 701-706
  
• Michail Vlachos, Dimitrios Gunopulos, Gautam Das:
  Rotation invariant distance measures for trajectories. 707-712
  
• Rebecca N. Wright, Zhiqiang Yang:
  Privacy-preserving Bayesian network structure computation on distributed heterogeneous data. 713-718
  
• Andrew Y. Wu, Michael Garland, Jiawei Han:
  Mining scale-free networks using geodesic clustering. 719-724
  
• Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, Hua Li, Zheng Chen, Wensi Xi, Weiguo Fan, Wei-Ying Ma, QianSheng Cheng:
  IMMC: incremental maximum margin criterion. 725-730
  
• Liang Huai Yang, Mong-Li Lee, Wynne Hsu, Xinyu Guo:
  2PXMiner: an efficient two pass mining of frequent XML query patterns. 731-736
  
• Lei Yu, Huan Liu:
  Redundancy based feature selection for microarray data. 737-742
  
• ChengXiang Zhai, Atulya Velivelli, Bei Yu:
  A cross-collection mixture model for comparative text mining. 743-748
  
• Ruofei Zhang, Zhongfei (Mark) Zhang, Sandeep Khanzode:
  A data mining approach to modeling relationships among categories in image collection. 749-754
  
• Zhiqiang Zheng, Balaji Padmanabhan, Haoqiang Zheng:
  A DEA approach for model combination. 755-760
  
• Michael Yu Zhu, Lei Liu:
  Optimal randomization for privacy preserving data mining. 761-766
  

Industry/government track posters

• Naoki Abe, Naval K. Verma, Chidanand Apté, Robert Schroko:
  Cross channel optimized marketing by reinforcement learning. 767-772
  
• Selim Aksoy, Krzysztof Koperski, Carsten Tusk, Giovanni B. Marchisio:
  Interactive training of advanced classifiers for mining remote sensing image archives. 773-782
  
• Christian Borgs, Jennifer T. Chayes, Mohammad Mahdian, Amin Saberi:
  Exploring the community structure of newsgroups. 783-787
  
• Erick Cantú-Paz, Shawn D. Newsam, Chandrika Kamath:
  Feature selection in scientific applications. 788-793
  
• Ian Davidson, Ashish Grover, Ashwin Satyanarayana, Giri Kumar Tayi:
  A general approach to incorporate data quality matrices into data mining algorithms. 794-798
  
• Nicolás de Abajo, Alberto B. Diez, Vanesa Lobato, Sergio R. Cuesta:
  ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study. 799-804
  
• Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong:
  A system for automated mapping of bill-of-materials part numbers. 805-810
  
• Satoshi Morinaga, Kenji Yamanishi:
  Tracking dynamics of topic trends using a finite mixture model. 811-816
  
• Takayuki Nakata, Jun-ichi Takeuchi:
  Mining traffic data from probe-car system for travel time prediction. 817-822
  
• Carlos Ordonez:
  Programming the K-means clustering algorithm in SQL. 823-828
  
• Dmitry Pavlov, Ramnath Balasubramanyan, Byron Dom, Shyam Kapur, Jignashu Parikh:
  Document preprocessing for naive Bayes classification and clustering with mixture of multinomials. 829-834
  
• Young Truong, Xiaodong Lin, Chris Beecher:
  Learning a complex metabolomic dataset using random forests and support vector machines. 835-840
  
• David S. Vogel, Morgan C. Wang:
  1-dimensional splines as building blocks for improving accuracy of risk outcomes models. 841-846
  
• Adam Yeh, Jonathan Tang, Youxuan Jin, Sam Skrivan:
  Analytical view of business data. 847-852
  

Last update Thu May 24 03:26:18 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page