Workshop Listing
853
KDD 2004 Workshops
BIOKDD04: Data Mining in Bioinformatics
Mohammed J. Zaki,
Rensselaer Polytechnic Institute, USA
Shinichi Morishita,
University of Tokyo, Japan
Isidore Rigoutsos,
IBM T.J. Watson Research Center, USA
TDM 2004: Mining Temporal and Sequential Data
K. P. Unnikrishnan,
General Motors R&D Center, USA
Ramasamy Uthurusamy,
General Motors IS&S, USA
Jiawei Han,
University of Illinois, USA
MRDM 2004: Multi-Relational Data Mining
Saso Dzeroski,
Jozef Stefan Institute, Slovenia
Hendrik Blockeel,
Katholieke Universiteit Leuven, Belgium
MDM/KDD 2004: Mining Integrated Media and Complex Data
Latifur Khan,
University of Texas at Dallas, USA
Valery A. Petrushin,
Accenture Technology Labs, USA
DM-SSP 2004: Data Mining Standards, Services and Platforms
Robert Grossman,
University of Illinois at Chicago/Open Data Partners, USA
Robert Chu,
SAS, USA
Mark Hornick,
Oracle, USA
Dustin Hux,
Elder Research Inc., USA
Dave Selinger,
Amazon.com, USA
Zhaohui Tang,
Microsoft, USA
Kurt Thearling,
Capital One, USA
LinkKDD 2004: Link Analysis and Group Detection
Jafar Adibi,
University of Southern California, USA
Hans Chalupsky,
University of Southern California, USA
Marko Grobelnik,
Jozef Stefan Institute, Slovenia
Natasa Milic-Frayling,
Microsoft Research, United Kingdom
Dunja Mladenic,
Jozef Stefan Institute, Slovenia
WebKDD 2004: Web Mining and Web Usage Analysis
Bamshad Mobasher,
DePaul University, USA
Bing Liu,
University of Illinois at Chicago, USA
Brij Masand,
Data Miners Inc., USA
Olfa Nasraoui,
University of Louisville, USA
MSW 2004: Mining for and from the Semantic Web
Andreas Hotho,
University of Kassel, Germany
York Sure,
University of Karlsruhe, Germany
Lise Getoor,
University of Maryland, USA
Tutorial Listing
Tutorials
Data Mining and Machine Learning in Time Series Databases
Eamonn Keogh, University of California-Riverside, USA
Data Quality and Data Cleaning: An Overview
Theodore Johnson, AT&T Labs Research, USA
Tamraparni Dasu, AT&T Labs Research, USA
Graph Structures in Data Mining
Soumen Chakrabarti, Indian Institute of Technology Bombay, India
Christos Faloutsos, Carnegie Mellon University, USA
Junk E-mail Filtering
Joshua Goodman, Microsoft Research, USA
Geoff Hulten, Microsoft, USA
Mining Unstructured Data
Ronen Feldman, Bar-Ilan University and ClearForest Corporation, Israel
Online Mining of Data Streams: Problems, Applications and Progress
Jian Pei, State University of New York at Buffalo, USA
Haixun Wang, IBM T. J. Watson Research Center, USA
Philip S. Yu, IBM T. J. Watson Research Center, USA
Panels Listing
855
Panels
Data Mining: Good, Bad, or Just a Tool?
Chair: Raghu Ramakrishnan, University of Wisconsin-Madison, USA
Panelists: Deirdre Mulligan, University of California Berkeley, USA
David Jensen, University of Massachusetts Amherst, USA
Michael J. Pazzani, National Science Foundation, USA
Rakesh Agrawal, IBM Almaden Research Center, USA
This panel is intended to be a forum to argue for continued efforts in developing data mining as a technology, while giving privacy advocates the opportunity to articulate their concerns. Three main issues will be discussed: (1) There is significant value to society in developing the science underpinning data mining, but also significant risk for misuse of the technology. The same techniques that could accurately identify malignant tumors could be used to classify individuals as potential terrorists, and the medical information that can be used to help doctors in emergency situations can also be used for invasive marketing. What should our response be? To disallow data mining altogether? To only apply it to “non-controversial” areas? To accept some risk if the need is acute or the benefits are compelling? (2) If our response is to develop data mining techniques and to apply them with care when appropriate or necessary, what checks and balances are required in order to safeguard individual rights? How can we constrain when and to what ends the technology is applied, and how the results are interpreted? What are the parallels to existing legal protections? What are the differences that make the problem of electronic privacy more challenging? (3) The Technology and Privacy Advisory Committee (TAPAC) recently issued its report. What are its main recommendations? How will, or should, it influence data mining research and practice?
Can Natural Language Processing Help Text Mining?
Chair: Anne Kao, Boeing Phantom Works, USA
Panelists:
Jaime Carbonell, Carnegie Mellon University, USA
Ken Church, Microsoft Research, USA
Oren Etzioni, University of Washington, USA
Nancy Lawler, Department of Defense, USA
Marko Grobelnik, Jozef Stefan Institute, Slovenia
Dave Lewis, David Lewis Consulting, USA
Giovanni Marchisio, Insightful Corporation, USA
Natural Language Processing (NLP) has been around for a number of decades. It has developed various techniques that are typically linguistically inspired, i.e. text is typically syntactically parsed using information from a formal grammar and a lexicon, the resulting information is then interpreted semantically and used to extract information about what was said. NLP may be deep or shallow, and even use statistical means to disambiguate word senses or multiple parses of the same sentence. It tends to focus on one document or piece of text at a time and be rather computationally expensive. It includes techniques like word stemming, multiword phrase grouping, synonym normalization, anaphora resolution, and role determination.
Text Mining is more recent, and uses techniques primarily developed in statistics and machine learning. Its aim typically is not to understand all or even a large part of what a given speaker/writer has said, but rather to extract patterns across a large number of documents. It includes things like text classification according to some fixed set of categories, automatic text clustering, extraction of topics from texts or groups of text and the analysis of trends.
In this panel, we will discuss (1) Can traditional NLP methods help text mining? If so, can they help all areas of text mining? Or just some areas? Which NLP areas/techniques are useful? (2) What is novel about text mining vs. NLP? In light of this, what would be some new future directions for NLP in light of requirements from text mining?
Author Index
Abe, N... 3, 767 Adachi, F. ... 486 Afrati, F. ... 12 Aggarwal, C. C. ... 503 Agichtein, E. ... 20 Agrawal, R... 611 Airoldi, E. ... 30 Aksoy, S... 773 Ali, K. ... 394 Alspector, J. ... 605 Anderson, B. ... 40 Apte, C... 767 Bagnall, A. J. ... 49 Balasubramanyan, R. ... 829 Banerjee, A. ... 509, 515 Basu, S. ... 59 Beecher, C. ... 835 Bennett, K. P... 521 Bi, J... 521 Bilenko, M. ... 59 Borgs, C. ... 783 Cantύ-Paz, E. ... 788 Cao, H... 236 Caruana, R. ... 69 Chakrabarti, D... 79 Chang, K. C.-C. ... 148 Chayes, J... 783 Chen, Z. ... 725 Cheng, H... 527 Cheng, Q... 725 Cheung, D. W. ... 236, 384 Chilson, J. ... 533 Chowdhury, A... 605 Clifton, C. ... 599 Cohen, W. W. ... 89 Cong, G... 226 Connolly, A. ... 40 Cuesta, S. R. ... 799 Cumby, C... 402 Cutler, A. ... 835 Dalvi, N. ... 99 Das, G. ... 707 Das, K. ... 539 Davidson, I... 545, 794 de Abajo, N... 799 Deng, L. ... 410 Dhillon, I... 509, 551 Diez, A. B. ... 799 Dom, B... 829 Domingos, P. ... 99 Elkan, C... 286 Ester, M. ... 557 Evgeniou, T. ... 109 Faloutsos, C...30, 79, 118, 653 Fan, W. ...128, 725 Fano, A. ... 402 Fujikawa, H. ... 486 Gade, K. ... 138 Gallagher, B. ... 593 Ganti, V. ... 20 Garland, M. ... 719 Gärtner, T. ... 158 Ge, R. ... 557 Ghani, R. ... 402 Ghosh, J... 509 Gilburd, B... 563 Gionis, A. ... 12 Griffiths, T... 306 Grover, A... 794 Guan, Y. ... 551 Gunopulos, D. ... 707 Guo, X. ... 731 Hadjieleftheriou, M. ... 236 Han, J...148, 503, 527, 617, 719 Haseltine, E. ... 1 He, B. ... 148 Heckerman, D... 2 Helm, R. F. ... 266 Homma, T... 486 Hooker, G. ...569, 575 Horváth, T. ... 158 Hsu, W... 731 Hu, M. ... 168 Hu, Z. ... 557 Huan, J... 581 Idé, T. ... 440 Iyengar, V. S... 587 Janacek, G. J... 49 Janardan, R. ...354, 364 Jaroszewicz, S. ... 178 Jeh, G... 187 Jensen, D. ... 593 Jiang, D. ... 430 Jin, J... 599 Jin, R. ... 695 Jin, W. ... 557 Jin, X. ... 197 Jin, Y. ... 847 Kabán, A. ...701 Kalagnanam, J...805 Kamath, C. ...450, 788 Kanapady, R...450 Kantarcioğlu, M. ...599 Kapur, S. ...829 Karr, A. F. ...677 Karypis, G. ...138 Kashima, H. ...440 Keogh, E. ...206, 460 Khanzode, S. ...749 Kok, J. N. ...647 Kołcz, A. ...605 Kollios, G...236 Kolter, J. Z. ...470 Koperski, K. ...773 Krema, M. ...402 Krishnapuram, R. ...611 Kulis, B. ...551 Kumar, D. ...266 Kumar, R...216 Kumar, V. ... 296, 334, 364, 459, 689 Kummamuru, K. ...611 Langford, J. ...3, 515 Lankford, J. P...460 Lazarevic, A...450 Lee, D. L. ...410 Lee, M. Li ...731 Li, C. ...226 Li, H. ...725 Li, Q. ...354, 364 Li, Y. ...617 Lin, J. ...460 Lin, X. ...677, 835 Liu, B. ...168, 494 Liu, H. ...737 Liu, J. ...623 Liu, L. ...761 Liu, T. ...629 Lobato, V. ...799 Lonardi, S...206, 460 Ma, J...410 Ma, W.-Y. ...725 Mahadevan, U. ...216 Mahdian, M...783 Maloof, M. A. ...470 Mamoulis, N. ...236, 384 Mannila, H. ...12, 683 Marchisio, G. ...773 Mausam...99 McCurley, K. S. ...118857 Mishra, B. ... 266 Mizil, A. N... 69 Mobasher, B... 197 Modha, D. S... 79, 509 Mooney, R. J... 59 Moore, A. W... 40, 539, 256, 629 Morinaga, S. ... 811 Motoda, H... 486 Muslea, I. ... 246 Nakashima, A. ... 486 Nakata, T. ... 817 Naphade, M. R... 641 Natsev, A. ... 641 Neill, D. B... 256 Neville, J... 593 Newsam, S. ... 788 Ng, R... 533 Nichol, R... 40 Niculescu-Mizil, A. ... 69 Nijssen, S. ... 647 Nystrom, D. M... 460 Ordonez, C... 823 Padmanabhan, B. ... 374, 755 Pan, J.-Y. ... 653 Papadimitriou, S. ... 79 Parikh, J. ... 829 Park, H. ... 364 Patek, M... 805 Paul, G. ... 545 Pavlov, D. ... 829 Pei, J... 316, 410, 430 Pontil, M. ... 109 Poole, D. ... 659 Popescul, A. ... 665 Potts, M... 266 Prins, J. ... 581 Ramakrishnan, N. ... 266 Ramanathan, M... 430 Ratanamahatana, C. A. ... 206 Reiter, J. P... 677 Rosen-Zvi, M... 306 Rusmevichientong, P. ... 671 Saberi, A. ... 783 Saidi, O. ... 479 Sanghai, S. ... 99 Sanil, A. P... 677 Sarawagi, S. ... 89 Satyanarayana, A. ... 794 Schaller, A... 494 Schneider, J. ... 539 Schroko, R... 767 Schuster, A. ... 563 Selinger, D... 671 Seppänen, J. K... 683 Shaham, E... 635 Shavlik, J. ... 276 Shavlik, M. ... 276 Shekhar, S... 334 Shi, B... 316 Shou, Y... 384 Simovici, D. A... 178 Singh, M. ... 805 Sivakumar, D... 216 Skrivan, S. ... 847 Smith, A. ... 286 Smith, J. R. ... 641 Smyth, P. ... 306 Srihari, R. ... 326 Steinbach, M...296, 689 Steyvers, M... 306 Sun, Y... 701 Takeuchi, J.-I... 817 Tamma, K... 459 Tan, P.-N. ...296, 334, 689, 695 Tang, C. ... 430 Tang, J. ... 847 Tao, Y... 236 Tayi, G. K... 794 Tiňo, P. ... 701 Tirpak, T. M. ... 494 Tomkins, A... 118 Truong, Y. ... 835 Tung, A. K. H... 226 Tusk, C. ... 773 Tuzhilin, A. ... 374 Ungar, L. H... 665 van Stam, W. ... 394 Velivelli, A. ... 743 Verbel, D. ... 479 Verma, D. ... 99 Verma, N. ... 767 Verma, S... 805 Vlachos, M. ... 707 Vogel, D. S. ... 841 Wagner, A. ... 533 Wang, C... 316 Wang, J...138, 503 Wang, M. C...841 Wang, S...226 Wang, W. ... 316, 581, 623 Washio, T...486 Widom, J...187 Wolff, R. ...563 Wong, Y. W. ...805 Wright, R. ...713 Wrobel, S. ...158 Wu, A. Y. ...719 Wu, X...326 Xi, W...725 Xiong, H... 334, 364, 689 Yamanishi, K. ...811 Yamazaki, K. ...486 Yan, J. ...725 Yan, L. ...479 Yan, S...725 Yan, X...527 Yang, G...344 Yang, H.-J. ...653 Yang, J. ... 581, 617, 623 Yang, K...629 Yang, L. H. ...731 Yang, Q...725 Yang, Z. ...713 Ye, J. ...354, 364 Yeh, A...847 Yoshida, K. ...486 Young, S. S. ...835 Yu, B...743 Yu, L. ...737 Yu, P. S. ...503 Zadrozny, B...3 Zamar, R. ...533 Zhai, C. X...743 Zhang, A. ...430 Zhang, B...725 Zhang, H. ...374 Zhang, R...749 Zhang, T...521 Zhang, X. ...384 Zhang, Z...749 Zhao, K. ...494 Zheng, H. ...755 Zheng, Z...755 Zhou, Y. ...197 Zhu, S...671 Zhu, Y. ...316, 761 Zvi, M. R...306
