Emerging Technologies in Knowledge Discovery and Data Mining: PAKDD 2007 International Workshops, Nanjing, China, May 22-25, 2007, Revised Selected

Front matter......Page 1
Workshop Overview......Page 13
Program Committee......Page 14
Introduction......Page 15
Data Mining and Data Mining Systems......Page 16
Survey of Open Source Data Mining Systems......Page 17
Important Features of Open Source Data Mining Systems......Page 18
Survey of Open Source Data Mining Systems......Page 19
Evaluation......Page 22
Conclusions......Page 25
Introduction......Page 27
Data......Page 28
Methodology......Page 29
Training......Page 30
Results......Page 33
Conclusion......Page 36
References......Page 37
Introduction......Page 39
Proposed Model......Page 40
The Algorithm......Page 41
Forecasting for TAIEX......Page 44
References......Page 45
Introduction......Page 47
Blog-Specific Search Engines......Page 49
Probabilistic Latent Semantic Analysis Model for Blog Mining......Page 50
Data Set......Page 52
Blog Search System......Page 53
Conclusions......Page 55
Introduction......Page 57
Turkish Language......Page 58
The Identification System......Page 59
Classifying Words and Word Groups......Page 60
The Discrimination Function......Page 61
Semantic Analysis and Sex Identification......Page 62
Results......Page 65
Conclusions and Future Work......Page 66
References......Page 67
Introduction......Page 68
Preparing Exceptional Behavior Data......Page 69
Positive/Negative Impact-Oriented Exceptional Behavior Patterns......Page 71
Impact-Contrasted Exceptional Behavior Patterns......Page 72
Experiments......Page 73
References......Page 75
Introduction......Page 76
Privacy-Preserving Data Publishing......Page 77
Privacy-Preserving (Distributed) Computation......Page 79
Weaknesses......Page 80
Privacy-Preserving Results Release......Page 81
Weaknesses......Page 83
Discussions and Possible Solutions......Page 84
Introduction......Page 88
Information Representation of High-Rise Structural Cases......Page 89
Structure of the High-Rise Case-Base......Page 90
General Process of Association Rules Mining......Page 91
Association Rule Mining for High-Rise Structure Form Selection......Page 92
Fuzzification of the Quantitative Attributes Intervals......Page 95
Application of Association Rules to Intelligent Structure Design......Page 96
References......Page 97
Introduction......Page 99
Survey of the CommonKADS Methodology......Page 101
CommonKADS Methodology Based PGSOS Knowledge Modeling......Page 102
Modeling Domain Knowledge......Page 103
Modeling Task Knowledge......Page 105
Modeling Inference Knowledge......Page 107
The Practical Applications......Page 109
References......Page 110
Introduction......Page 111
Problems and Framework......Page 113
Least Square Fitting (LSF)......Page 114
Neural Networks......Page 115
Model Optimisation......Page 116
Prediction Model Selection......Page 118
Model Optimisation......Page 119
Conclusions......Page 120
Introduction......Page 122
Program Co-chairs......Page 123
Introduction......Page 124
Former Method and Its Disadvantages......Page 125
The New Method......Page 126
Testing......Page 128
References......Page 129
Introduction......Page 131
Method......Page 133
The Karate Club Network......Page 135
The Football Team Network......Page 136
The Scientific Collaboration Network......Page 137
A Protein-Protein Interaction Network......Page 138
Conclusion......Page 141
Introduction......Page 143
The General HIV Dynamical Model......Page 144
New Forecast Model......Page 145
Observation Functions......Page 147
Data......Page 148
Results......Page 149
Conclusion......Page 152
References......Page 153
Introduction......Page 154
Cell Lines, Chemicals, Antibodies, Apparatus......Page 155
Cytoplasmic and Nuclear Protein Extracts......Page 156
Silver Staining in Arraytube......Page 157
Results......Page 158
Discussion......Page 162
Conclusions......Page 163
References......Page 164
Introduction......Page 165
Feature Extraction Based on Wavelets......Page 166
Support Vector Machine (SVM)......Page 167
Experiments and Results......Page 168
References......Page 171
Introduction......Page 174
Implementation......Page 176
Dictionaries......Page 177
Incorporating Dictionary Features......Page 178
Impact of Coverage and Noises......Page 179
Experiment 1......Page 181
Experiment 4......Page 182
Conclusions and Future Work......Page 183
Introduction......Page 186
Apriori Based Mining of Frequent Trajectories......Page 187
Translational and Rotational Invariant Mining......Page 190
Wavelet Based Optimization of Mining Speed......Page 192
Experiments......Page 193
Conclusions......Page 196
Introduction......Page 198
The Off-lattice AB Model......Page 199
Initial Conformation Mechanism......Page 200
Genetic-Annealing Algorithm......Page 201
Experimental Results......Page 203
Conclusion......Page 204
References......Page 205
Introduction......Page 206
Biclustering with Singular Value Decomposition......Page 208
Parameters Estimation......Page 211
Experiments and Analysis......Page 213
Conclusion......Page 216
Introduction......Page 218
Notions......Page 219
Partial Least Squares Based Dimension Reduction......Page 220
Date Sets......Page 222
Evaluation Methods......Page 223
The Influence of Dimensional Size......Page 224
Model Selection by $R_y^2$......Page 226
Conclusions......Page 227
Introduction......Page 230
ECG Biosignal Processing......Page 231
Linear Feature......Page 232
Nonlinear Feature......Page 233
Preprocessing Step......Page 235
Supervised Methods......Page 236
Experimental Results......Page 237
References......Page 239
Introduction......Page 241
Organization......Page 242
Introduction......Page 243
Preliminaries......Page 245
Pattern Summarization Tree......Page 246
Maintenance of PS-tree......Page 247
Recently Representative Patterns Mining......Page 250
Performance Study......Page 251
References......Page 254
Introduction......Page 256
Our Contribution......Page 257
The Counting Bloom Filter......Page 258
Our Algorithm......Page 259
Experiments Study......Page 264
Conclusion......Page 266
Introduction......Page 268
Related Work......Page 269
VFDT......Page 270
VFDTc......Page 271
Updates the Threaded Search Binary Tree While New Examples Arrives......Page 273
Threads the Binary Tree While New Example Arrives......Page 274
Best Split-Test Point Selecting......Page 275
Evaluation......Page 276
Conclusions and Future Work......Page 277
References......Page 278
Introduction......Page 280
Related Work......Page 282
Preliminaries......Page 283
Analysis......Page 284
Sorted-Based Subspace Skyline Clusters Mining......Page 285
Threshold-Based Subspace Skyline Clusters Mining......Page 286
Experimental Results......Page 288
References......Page 291
Introduction......Page 292
Related Work and Background......Page 293
Preliminaries......Page 294
Our Protocol......Page 295
Complexity Analysis......Page 298
Implementation and Performance Evaluation......Page 299
Discussions and Conclusion......Page 302
Introduction......Page 304
Definitions and Theorems......Page 305
Algorithm......Page 308
Experiments......Page 310
Conclusion and Future Work......Page 311
References......Page 312
Introduction......Page 313
Preliminary......Page 314
Basic Definitions......Page 315
Transform Amerge Tree to a Common Tree......Page 316
Operations to a Merge Tree......Page 317
Obtain the Common Tree......Page 318
Measuring the Similarity Between XML Documents......Page 320
Experiments......Page 321
Conclusions and Future Work......Page 322
References......Page 323
Introduction......Page 324
Ensemble Learning......Page 325
Derivation of Distributed Clustering Model......Page 326
DK-Means......Page 328
Experimental Results......Page 329
References......Page 332
Introduction......Page 334
Data Service Discovery......Page 336
Data Mining Facilities......Page 338
Database Connection Management......Page 340
Conclusion......Page 341
References......Page 342
Introduction......Page 344
General Idea......Page 345
Preprocessing......Page 346
Feature Space Transformation......Page 347
Transformation Clustering......Page 348
Evaluation......Page 350
Synthesis Datasets......Page 351
Real Life Datasets......Page 352
Parameters......Page 353
References......Page 354
Introduction......Page 356
Ant Colony Optimization......Page 358
Using Improved ACO to Get the Shortest Obstructed Distance......Page 359
Particle Swarm Optimization......Page 361
PKSCOC Based on PSO and K-Medoids......Page 362
PKSCOC Based on PSO and K-Medoids......Page 363
Results and Discussion......Page 364
Conclusions......Page 366
References......Page 367
Introduction......Page 369
Cube Segmentation......Page 370
Prefix Bitmap Indexing......Page 372
Parallel Construction of Shell Cube Segments......Page 374
Efficient OLAP Query Handling......Page 376
Performance Study......Page 377
Conclusions......Page 378
References......Page 379
Introduction......Page 380
Related Concepts......Page 381
GCOD Algorithm......Page 383
Experimental Results......Page 386
Correctness Test......Page 387
Conclusion......Page 388
Introduction......Page 390
Frequent Pattern Tree with a Children Table......Page 392
Depth First Generation of Frequent Patterns Algorithm......Page 394
Analysis of DF_Miner......Page 395
Performance Study......Page 397
References......Page 400
Introduction......Page 401
Storage Modules in Grid Monitoring System......Page 402
Classification Algorithm......Page 403
Characteristics of Monitoring Data......Page 404
Time Series Index Algorithms in PLR......Page 406
Analysis of Algorithms......Page 407
Performance and Effect of Index Algorithm in PLR......Page 408
References......Page 411
Related Works......Page 413
Best-Match Method Used in Co-training Algorithm......Page 414
Experimental Results......Page 417
Conclusion and Future Works......Page 419
Introduction......Page 422
Design of Fitness Function......Page 423
Genetic Operation......Page 424
Process of Simulated Annealing......Page 425
A New Weighted Vector Space Model for Classifying Documents......Page 426
Experiments and Results......Page 428
Conclusion......Page 431
Introduction......Page 433
Related Work......Page 434
Architecture......Page 435
User Space Service......Page 436
Replication Management Service......Page 437
Transfer Client......Page 438
Data Transfer Performance......Page 440
References......Page 443
Introduction......Page 445
Related Works......Page 446
Utility Mining Model......Page 447
Utility-Frequent Mining Model......Page 449
Algorithms......Page 451
Experimental Results......Page 453
Conclusion......Page 455
Introduction......Page 457
Incremental Frequent Patterns Mining with the Change of Minimum Support Threshold......Page 458
Incremental Frequent Patterns Mining with the Change of Minimum Support Threshold......Page 459
Dynamic Frequent Patterns Tree with a Children Table and a Trailer Table......Page 460
Top-Down Strategy for Mining Frequent Patterns......Page 462
Reconstruction of DFP_tree......Page 463
Bottom-Up Strategy for Incremental Maintenance of Frequent Patterns......Page 464
Performance Study......Page 465
References......Page 468
Introduction......Page 469
Problem Definition......Page 470
Algorithm Overview......Page 471
Add a Transaction to the Sliding Window......Page 472
Delete a Transaction from the Sliding Window......Page 475
Performance Evaluation......Page 478
Conclusions and Future Work......Page 479
Introduction......Page 481
K-Means......Page 482
Clustering and Merging Large Quantities of Bioinformatics Data in Distributed Environments......Page 483
Evaluation......Page 484
Conclusion......Page 486
References......Page 487
Introduction......Page 488
Definitions, Notations and Related Works......Page 489
Basic Idea and Method......Page 490
Acceleration of Pruning......Page 492
Diameter Pruning......Page 493
Experiment Result......Page 494
References......Page 495
Introduction......Page 496
Related Works......Page 497
Model of the Dependency Based Retrieval......Page 498
Parameter Estimations......Page 499
Experiments......Page 500
References......Page 502
Introduction......Page 504
Related Work......Page 505
Trustworthiness of Factoid......Page 506
Factoid Ranking......Page 507
Experiments and Results Analysis......Page 510
References......Page 511
Introduction......Page 512
Program Committee......Page 513
Introduction......Page 514
Research Motivations......Page 516
Functional Trust rho_{ij}^F......Page 517
Similarity $rho_{ij}^S$ and Truthfulness $rho_{ij}^T$ in Referral Trust......Page 518
Emergence of Properties of Social Trust Network......Page 519
Simulation Results......Page 522
Conclusion and Future Works......Page 524
References......Page 525
Introduction......Page 527
Related Works......Page 528
System Setting......Page 529
Secure Clock Synchronization......Page 530
Protocol Detail......Page 531
Number of Verifiers......Page 534
Performance Analysis and Simulation Result......Page 535
Conclusion......Page 537
Introduction......Page 539
Researches on Key Pre-distribution: Survey......Page 540
Grid-Based KPD with Plat Polynomial Assignment......Page 541
Keying Material Assignment and Identifiers Structure......Page 542
Distribution of Communication......Page 543
Memory Overhead......Page 544
Communication Overhead......Page 545
Security Analysis......Page 546
Comparison with Other Schemes......Page 547
Conclusions......Page 548
Introduction......Page 550
Related Work......Page 551
Local Data Collection......Page 552
Local Detection......Page 554
Cooperative Detection......Page 555
Simulation Results......Page 557
References......Page 561
Introduction......Page 562
Related Work......Page 563
Dynasa: Adaptive Framework......Page 564
Situations for Adaptation......Page 567
Adaptive Policies and Plans......Page 568
Simulations......Page 570
Conclusion and Future Work......Page 571
Introduction......Page 574
Related Work......Page 575
Designing Scheduling Protocols by Employing Edge Coloring Technique......Page 577
A Graph Model for Inter-piconet and Intra-piconet Delay......Page 580
Simulation Results......Page 582
References......Page 584
Introduction......Page 586
Security Threats to RFID System......Page 587
Review of OHLCAP......Page 588
Description of OHLCAP......Page 589
Traceability Using Counter Information......Page 590
Physical Attack on Tag......Page 591
Group-Based Low-Cost Authentication Protocol......Page 592
Security and Efficiency Analysis......Page 593
Conclusion......Page 594
Introduction......Page 596
Design and Implementation of an Active RFID Reader Based on a Cache of Tag Memory Data......Page 597
An Active RFID Reader Based on the Standards......Page 598
An Active RFID Reader Based on a Cache of Tag Memory Data......Page 599
Experiments and Analyses......Page 602
Analyses of Processing Time and Transmission Rate......Page 603
Cache Coherence Experiments......Page 605
Conclusions and Future Work......Page 606
Introduction......Page 608
Security Threats......Page 609
Related Works......Page 610
LCAP (Low-Cost Authentication Protocol)......Page 611
Parameters......Page 612
RFID Privacy Protect Protocols 1......Page 613
RFID Privacy Protect Protocols 2......Page 614
Analysis......Page 616
Requirements Measures......Page 617
Conclusion......Page 618
References......Page 619
Introduction......Page 620
Background of LU Matrix-Based Key Pre-distribution......Page 622
The Network Model......Page 623
The Hierarchical Composition of LU Matrix-Based Key Distribution Scheme......Page 624
Remediations......Page 626
Security Analysis......Page 627
Performance Evaluation......Page 628
Conclusion......Page 631
Introduction......Page 633
Security Framework for Home Network......Page 634
Authentication......Page 635
Authorization......Page 636
Security Policy......Page 638
Conclusion......Page 639
References......Page 640
Introduction......Page 641
Location-Based Key Management Scheme......Page 642
Generation and Distribution of Cell Keys......Page 643
Improvement......Page 644
Report Generation and En-Route Filtering......Page 645
Overhead Analysis......Page 646
Conclusion......Page 647
Introduction......Page 648
Multipath Routing Protocol......Page 649
Scalable Audio Coding......Page 651
Performance Evaluations......Page 652
Simulation Results......Page 653
Conclusions and Future Work......Page 654
Introduction......Page 656
Wavelets Summarization......Page 657
Data Based and Query Based Estimation Error......Page 659
Flexible Adjustment of the Storage Limit $m$......Page 660
Experimental Setup......Page 662
Flexible vs Fixed Storage Allocation......Page 664
Related Work......Page 665
Conclusions......Page 666
References......Page 667
Introduction......Page 668
Related Work......Page 669
Extended Usage Control Model ({UCON}_{ABCD})......Page 670
SSO Using Delegation of Access Rights......Page 671
Conclusion......Page 673
References......Page 674
Introduction......Page 676
The Framework of PDRM System......Page 677
The Modules in PDRM System......Page 678
Content Packaging......Page 679
Right Agent with Distributed-Centralized Structure......Page 680
References......Page 683
Back matter......Page 685