3. PAKDD 1999: Beijing, China

@proceedings{DBLP:conf/pakdd/1999,
  editor    = {Ning Zhong and
               Lizhu Zhou},
  title     = {Methodologies for Knowledge Discovery and Data Mining, Third
               Pacific-Asia Conference, PAKDD-99, Beijing, China, April 26-28,
               1999, Proceedings},
  booktitle = {PAKDD},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {1574},
  year      = {1999},
  isbn      = {3-540-65866-1},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Invited Talks

• Won Kim:
  KDD as an Enterprise IT Tool: Reality and Agenda (Abstract). 1
  
• Hiroshi Motoda:
  Computer Assisted Discovery of First Principle Equations from Numeric Data (Abstract). 2
  

Emerging KDD Technology

• Zdzislaw Pawlak:
  Data Mining - a Rough Set Perspective. 3-12
  
• Charu C. Aggarwal, Philip S. Yu:
  Data Mining Techniques for Associations, Clustering and Classification. 13-23
  
• Tsau Young Lin:
  Data Mining: Granular Computing Approach. 24-33
  
• Hiroshi Tsukimoto:
  Rule Extraction from Prediction Models. 34-43
  

Association Rules

• Xiaoyong Du, Zhibin Liu, Naohiro Ishii:
  Mining Association Rules on Related Numeric Attributes. 44-53
  
• Chi Lap Yip, K. K. Loo, Ben Kao, David Wai-Lok Cheung, C. K. Cheng:
  LGen - A Lattice-Based Candidate Set Generation Algorithm for I/O Efficient Association Rule Mining. 54-63
  
• Karthick Rajamani, Sam Yuan Sung, Alan L. Cox:
  Extending the Applicability of Association Rules. 64-73
  
• Pauray S. M. Tsai, Chih-Chong Lee, Arbee L. P. Chen:
  An Efficient Approach for Incremental Association Rule Mining. 74-83
  
• Marzena Kryszkiewicz:
  Association Rules in Incomplete Databases. 84-93
  
• Iko Pramudiono, Takahiko Shintani, Takayuki Tamura, Masaru Kitsuregawa:
  Parallel SQL Based Association Rule Mining on Large Scale PC Cluster: Performance Comparison with Directly Coded C Implementation. 94-98
  
• Yuping Yang, Mukesh Singhal:
  H-Rule Mining in Heterogeneous Databases. 99-103
  
• Aoying Zhou, Shuigeng Zhou, Wen Jin, Zengping Tian:
  An Improved Definition of Multidimensional Inter-transaction Association Rule. 104-108
  
• Keyun Hu, Yuchang Lu, Chunyi Shi:
  Incremental Discovering Association Rules: A Concept Lattice Approach. 109-113
  

Feature Selection and Generation

• Xindong Wu:
  Induction as Pre-processing. 114-122
  
• Zijian Zheng, Geoffrey I. Webb:
  Stochastic Attribute Selection Committees with Aultiple Boosting: Learning More Accurate and More Stable Classifer Committees. 123-132
  
• Yiyu Yao, S. K. Michael Wong, Cory J. Butz:
  On Information-Theoretic Measures of Attribute Importance. 133-137
  
• Kee-Cheol Lee:
  A Technique of Dynamic Feature Selection Using the Feature Group Mutual Information. 138-142
  
• Masahiro Terabe, Osamu Katai, Tetsuo Sawaragi, Takashi Washio, Hiroshi Motoda:
  A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree. 143-147
  

Mining in Semi, Un-structured Data

• Lisa Singh, Bin Chen, Rebecca Haight, Peter Scheuermann:
  An Algorithm for Constrained Association Rule Mining in Semi-structured Data. 148-158
  
• Aoying Zhou, Wen Jin, Shuigeng Zhou, Zengping Tian:
  Incremental Mining of Schema for Semistructured Data. 159-168
  
• Mon-Fong Jiang, Shian-Shyong Tseng, Chang-Jiun Tsai:
  Discovering Structure from Document Databases. 169-173
  
• Vincent Cho, Beat Wüthrich:
  Combining Forecasts from Multiple Textual Data Sources. 174-178
  
• Xiaofeng Meng, Yong Zhou, Shan Wang:
  Domain Knowledge Extracting in a Chinese Natural Language Interface to Databases: NChiql. 179-183
  

Interestingness, Surprisingness, and Exceptions

• Graham J. Williams:
  Evolutionary Hot Spots Data Mining - An Architecture for Exploring for Interesting Discoveries. 184-193
  
• Huan Liu, Hongjun Lu, Ling Feng, Farhad Hussain:
  Efficient Search of Reliable Exceptions. 194-203
  
• Robert J. Hilderman, Howard J. Hamilton:
  Heuristic for Ranking the Interestigness of Discovered Knowledge. 204-209
  

Rough Sets, Fuzzy Logic, and Neural Networks

• Shusaku Tsumoto:
  Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusion. 210-219
  
• Zongtian Liu, Zhipeng Xie:
  Discernibility System in Rough Sets. 220-227
  
• Andreas Rauber, Dieter Merkl:
  Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal Its Secrets. 228-237
  
• Ling Zhang, Bo Zhang:
  Neural Network Based Classifers for a Vast Amount of Data. 238-246
  
• Hércules Antonio do Prado, Karla F. Machado, Sandra R. Frigeri, Paulo Martins Engel:
  Accuracy Tuning on Combinatorial Neural Model. 247-251
  
• Yoshitsugu Kakemoto, Shinichi Nakasuka:
  A Situated Information Articulation Neural Network: VSF Network. 252-257
  
• Chao Deng, Fanlun Xiong:
  Neural Method for Detection of Complex Patterns in Databases. 258-262
  
• Xuemei Shi, Man-chung Chan, Deyi Li:
  Preserve Discovered Linguistic Patterns Valid in Volatility Data Environment. 263-267
  
• Daisuke Shibata, Nobuhiro Inuzuka, Shohei Kato, Tohgoroh Matsui, Hidenori Itoh:
  An Induction Algorithm Based on Fuzzy Logic Programming. 268-273
  
• Shusaku Tsumoto:
  Rule Discovery in Databases with Missing Values Based on Rough Set Model. 274-278
  
• Xuefei Wang, Rusong Wang, Jue Wang:
  Sustainability Knowledge Mining from Human Development Database. 279-283
  

Induction, Classification, and Clustering

• Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio:
  Characterization of Default Knowledge in Ripple Down Rules Method. 284-295
  
• Kai Ming Ting, Zijian Zheng:
  Improving the Performance of Boosting for Naive Bayesian Classification. 296-305
  
• Douglas A. Newlands, Geoffrey I. Webb:
  Convex Hulls in Concept Induction. 306-316
  
• Jianhua Fan, Deyi Li:
  Mining Classification Knowledge Based on Cloud Models. 317-326
  
• Vladimir Estivill-Castro, Michael E. Houle:
  Robust Clustering of Large Geo-referenced Data Sets. 327-337
  
• Bo Zhou, David Wai-Lok Cheung, Ben Kao:
  A Fast Algorithm for Density-Based Clustering in Large Database. 338-349
  
• Gabor Melli:
  A Lazy Model-Based Algorithm for On-Line Classification. 350-354
  
• Khaled Alsabti, Sanjay Ranka, Vineet Singh:
  An Efficient Space-Partitioning Based Algorithm for the K-Means Clustering. 355-359
  
• Chih-Ming Su, Shian-Shyong Tseng, Mon-Fong Jiang, Joe C. S. Chen:
  A Fast Clustering Process for Outliers and Remainder Clusters. 360-364
  
• Hongxing He, Simon Hawkins:
  Optimising the Distance Metric in the Nearest Neighbour Algorithm on a Real-World Patient Classification Problem. 365-369
  
• Zijian Zheng, Boon Toh Low:
  Classifying Unseen Cases with Many Missing Values. 370-374
  
• Tu Bao Ho, Ngoc Binh Nguyen, Takafumi Morita:
  Study of a Mixed Similarity Measure for Classification and Clustering. 375-379
  

Visualization

• Bing Liu, Wynne Hsu, Ke Wang, Shu Chen:
  Visually Aided Exploration of Interesting Association Rules. 380-389
  
• Jianchao Han, Nick Cercone:
  DVIZ: A System for Visualizing Data Mining. 390-399
  

Causal Model and Graph-Based Methods

• Honghua Dai:
  A Minimal Causal Model Learner. 400-408
  
• K. L. Lee, Guanling Lee, Arbee L. P. Chen:
  Efficient Graph-Based Algorithm for Discovering and Maintaining Knowledge in Large Databases. 409-419
  
• Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda, Kouhei Kumasawa, Naohide Arai:
  Basket Analysis for Graph Structured Data. 420-431
  
• Julian R. Neil, Kevin B. Korb:
  The Evolution of Causal Models: A Comparison of Bayesian Metrics and Structure Priors. 432-437
  
• Tetsuhiro Miyahara, Tomoyuki Uchida, Tetsuji Kuboyama, Tasuya Yamamoto, Kenichi Takahashi, Hiroaki Ueda:
  KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System. 438-442
  

Agent-Based, and Distributed Data Mining

• Yike Guo, Janjao Sutiwaraphun:
  Probing Knowledge in Distributed Data Mining. 443-452
  
• Zbigniew W. Ras, Jan M. Zytkow:
  Discovery of Equations and the Shared Operational Semantics in Distributed Autonomous Databases. 453-463
  
• Djamel A. Zighed, Myriam Côté, Nader Troudi:
  The Data-Mining and the Technology af Agents to Fight the Illicit Electronic Messages. 464-468
  
• Hongen Lu, Leon Sterling, Alex Wyatt:
  Knowledge Discovery in SportsFinder: An Agent to Extract Sports Results from the Web. 469-473
  
• Louis Perrochon, Walter Mann, Stephane Kasriel, David C. Luckham:
  Event Mining with Event Processing Networks. 474-478
  

Advanced Topics and New Methodologies

• Yiyu Yao, Ning Zhong:
  An Analysis of Quantitative Measures Associated with Rules. 479-488
  
• Jingde Cheng:
  A Strong Relevant Logic Model of Epistemic Processes in Scientific Discovery (Extended Abstract). 489-493
  
• Tetsuya Yoshida, Teruyuki Kondo, Shogo Nishida:
  Discovering Conceptual Differences among Different People via Diverse Structures. 494-498
  
• Oscar Ortega Lobo, Masayuki Numao:
  Ordered Estimation of Missing Values. 499-503
  
• Einoshin Suzuki, Toru Ohno:
  Prediction Rule Discovery Based on Dynamic Bias Selection. 504-508
  
• Aijun An, Nick Cercone:
  Discretization of Continuous Attributes for Learning Classification Rules. 509-514
  
• Sadok Ben Yahia, Ali Jaoua:
  BRRA: A Based Relevant Rectangles Algorithm for Mining Relationships in Databases. 515-519
  
• Xiaopeng Tao, Ning Wang, Shuigeng Zhou, Aoying Zhou, Yunfa Hu:
  Mining Functional Dependency Rule of Relational Database. 520-524
  
• Rong Jiang, Deyi Li, Hui Chen:
  Time-Series Prediction with Cloud Models in DMKD. 525-529