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From AAAI Press:
Data Mining
Next Generation Challenges and Future Directions
Edited by Hillol Kargupta, Anupam Joshi, Krishnamoorthy Sivakumar and Yelena Yesha
| Foreword | ix |
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| Preface | xiii |
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| Pervasive, Distributed, and Stream Data Mining | |
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| 1 | Existential Pleasures of Distributed Data Mining
Hillol Kargupta and Krishnamoorthy Sivakumar | 3 |
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| 2 | Research Issues in Mining and Monitoring of Intelligence Data
Alan Demers, Johannes Gehrke and Mirek Riedewald | 27 |
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| 3 | A Consensus Framework for Integrating Distributed Clusterings under Limited Knowledge Sharing
Joydeep Ghosh, Alexander Strehl and Srujana Merugu | 47 |
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| 4 | Design of Distributed Data Mining Applications on the Knowledge Grid
Mario Cannataro, Domenico Talia and Paolo Trunfio | 67 |
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| 5 | Photonic Data Services: Integrating Data, Network and Path Services to Support Next Generation Data Mining Applications
Robert L. Grossman, Yunhong Gu, Dave Hanley, Xinwei Hong, Jorge Levera, Marco Mazzucco, David Lillethun, Joe Mambretti and Jeremy Weinberger | 89 |
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| 6 | Mining Frequent Patterns in Data Streams at Multiple Time Granularities
Chris Giannella, Jiawei Han, Jian Pei, Xifeng Yan and Philip S. Yu | 105 |
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| 7 | Efficient Data-Reduction Methods for On-Line Association Rule Discovery
Hervé Brönnimann, Bin Chen, Manoranjan Dash, Peter Haas and Peter Scheuermann | 125 |
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| 8 | Discovering Recurrent Events in Multichannel Data Streams Using Unsupervised Methods
Milind R. Naphade, Chung-Sheng Li and Thomas S. Huang | 147 |
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| Counterterrorism, Privacy, and Data Mining | |
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| 9 | Data Mining for Counterterrorism
Bhavani Thuraisingham | 157 |
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| 10 | Biosurveillance and Outbreak Detection
Paola Sebastiani and Kenneth D. Mandl | 185 |
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| 11 | MINDS -- Minnesota Intrusion Detection System
Levent Ertöz, Eric Eilertson, Aleksandar Lazarevic, Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava and Paul Dokas | 199 |
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| 12 | Marshalling Evidence through Data Mining in Support of Counter Terrorism
Daniel Barbará, James J. Nolan, David Schum and Arun Sood | 219 |
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| 13 | Relational Data Mining with Inductive Logic Programming for Link Discovery
Raymond J. Mooney, Prem Melville, Lappoon Rupert Tang, Jude Shavlik, Inęs de Castro Dutra, David Page and Vítor Santos Costa | 239 |
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| 14 | Defining Privacy for Data Mining
Chris Clifton, Murat Kantarcioglu and Jaideep Vaidya | 255 |
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| Scientific Data Mining | |
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| 15 | Mining Temporally-Varying Phenomena in Scientific Datasets
Raghu Machiraju, Srinivasan Parthasarathy, John Wilkins, David S. Thompson, Boyd Gatlin, David Richie, Tat-Sang S. Choy, Ming Jiang, Sameep Mehta, Matthew Coatney, Stephen A. Barr and Kaden Hazzard | 273 |
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| 16 | Methods for Mining Protein Contact Maps
Mohammed J. Zaki, Jingjing Hu and Chris Bystroff | 291 |
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| 17 | Mining Scientific Data Sets Using Graphs
Michihiro Kuramochi, Mukund Deshpande and George Karypis | 315 |
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| 18 | Challenges in Environmental Data Warehousing and Mining
Nabil R. Adam, Vijayalakshmi Atluri, Dihua Guo and Songmei Yu | 335 |
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| 19 | Trends in Spatial Data Mining
Shashi Shekhar, Pusheng Zhang, Yan Huang and Ranga Raju Vatsavai | 357 |
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| 20 | Challenges in Scientific Data Mining: Heterogenous, Biased, and Large Samples
Zoran Obradovic and Slobodan Vucetic | 381 |
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| Web, Semantics, and Data Mining | |
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| 21 | Web Mining -- Concepts, Applications, and Research Directions
Jaideep Srivastava, Prasanna Desikan and Vipin Kumar | 405 |
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| 22 | Advancements in Text Mining Algorithms and Software
Svetlana Y. Mironova, Michael W. Berry, Scott Atchley and Micah Beck | 425 |
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| 23 | On Data Mining, Semantics, and Intrusion Detection, What to Dig for and Where to Find It
Anupam Joshi and Jeffrey L. Undercoffer | 437 |
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| 24 | Usage Mining for and on the Semantic Web
Bettina Berendt, Gerd Stumme and Andreas Hotho | 461 |
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| Bibliography | 481 |
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| Index | 533 |
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