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ORCID6. PAKDD 2002: Taipei, Taiwan
- Ming-Shan Cheng, Philip S. Yu, Bing Liu:
Advances in Knowledge Discovery and Data Mining, 6th Pacific-Asia Conference, PAKDD 2002, Taipei, Taiwan, May 6-8, 2002, Proceedings. Lecture Notes in Computer Science 2336, Springer 2002, ISBN 3-540-43704-5
Industrial Papers (Invited)
- Minos N. Garofalakis, Rajeev Rastogi:
Network Data Mining and Analysis: The NEMESIS Project. 1-12 - Ramakrishnan Srikant:
Privacy Preserving Data Mining: Challenges and Opportunities. 13
Survey Papers (Invited)
- Jaideep Srivastava, Jau-Hwang Wang, Ee-Peng Lim
, San-Yih Hwang:
A Case for Analytical Customer Relationship Management. 14-27 - Osmar R. Zaïane, Andrew Foss, Chi-Hoon Lee, Weinan Wang:
On Data Clustering Analysis: Scalability, Constraints, and Validation. 28-39
Association Rules (I)
- Jacinto Mata Vázquez, José Luis Álvarez Macías, José Cristóbal Riquelme Santos:
Discovering Numeric Association Rules via Evolutionary Algorithm. 40-51 - Jochen Hipp, Christoph Mangold, Ulrich Güntzer, Gholamreza Nakhaeizadeh:
Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining. 52-65 - Qin Ding, Qiang Ding, William Perrizo:
Association Rule Mining on Remotely Sensed Images Using P-trees. 66-79 - Vikram Pudi, Jayant R. Haritsa:
On the Efficiency of Association-Rule Mining Algorithms. 80-91
Classification (I)
- Jung-Yi Lin, Been-Chian Chien, Tzung-Pei Hong:
A Function-Based Classifier Learning Scheme Using Genetic Programming. 92-103 - Zhipeng Xie, Wynne Hsu, Zongtian Liu, Mong-Li Lee:
SNNB: A Selective Neighborhood Based Naïve Bayes for Lazy Learning. 104-114 - Lili Diao, Keyun Hu, Yuchang Lu, Chunyi Shi:
A Method to Boost Naïve Bayesian Classifiers. 115-122 - Charles X. Ling, Huajie Zhang:
Toward Bayesian Classifiers with Accurate Probabilities. 123-134
Interestingness
- Szymon Jaroszewicz, Dan A. Simovici:
Pruning Redundant Association Rules Using Maximum Entropy Principle. 135-147 - Wen-Yang Lin, Ming-Cheng Tseng, Ja-Hwung Su:
A Confidence-Lift Support Specification for Interesting Associations Mining. 148-158 - Marzena Kryszkiewicz, Marcin Gajek:
Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators. 159-171 - Show-Jane Yen, Yue-Shi Lee:
Mining Interesting Association Rules: A Data Mining Language. 172-176 - Robert J. Hilderman:
The Lorenz Dominance Order as a Measure of Interestingness in KDD. 177-185
Sequence Mining
- Minghua Zhang, Ben Kao, David Wai-Lok Cheung, Chi Lap Yip:
Efficient Algorithms for Incremental Update of Frequent Sequences. 186-197 - Ming-Yen Lin, Suh-Yin Lee, Sheng-Shun Wang:
DELISP: Efficient Discovery of Generalized Sequential Patterns by Delimited Pattern-Growth Technology. 198-209 - Jafar Adibi, Wei-Min Shen, Eaman Noorbakhsh:
Self-Similarity for Data Mining and Predictive Modeling - A Case Study for Network Data. 210-217 - Shun-Chieh Lin, Shian-Shyong Tseng, Yao-Tsung Lin:
A New Mechanism of Mining Network Behavior. 218-223
Clustering
- Michael K. Ng, Joshua Zhexue Huang:
M-FastMap: A Modified FastMap Algorithm for Visual Cluster Validation in Data Mining. 224-236 - Chien-Yu Chen, Shien-Ching Hwang, Yen-Jen Oyang:
An Incremental Hierarchical Data Clustering Algorithm Based on Gravity Theory. 237-250 - Ah-Hwee Tan, Hong Pan:
Adding Personality to Information Clustering. 251-256 - François-Xavier Jollois, Mohamed Nadif:
Clustering Large Categorical Data. 257-263
Web Mining
- Tong Zheng, Yonghe Niu, Randy Goebel:
WebFrame: In Pursuit of Computationally and Cognitively Efficient Web Mining. 264-275 - Bowo Prasetyo, Iko Pramudiono, Katsumi Takahashi, Masaru Kitsuregawa:
Naviz : Website Navigational Behavior Visualizer. 276-289 - Zhixiang Chen, Ada Wai-Chee Fu, Frank Chi-Hung Tong:
Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs. 290-296 - Chia-Hui Chang, Shih-Chien Kuo, Kuo-Yu Huang, Tsung-Hsin Ho, Chih-Lung Lin:
Automatic Information Extraction for Multiple Singular Web Pages. 297-303
Association Rules (II)
- Honghua Dai, Gang Li:
An Improved Approach for the Discovery of Causal Models via MML. 304-315 - Ye-In Chang, Yu-Ming Hsieh:
SETM*-MaxK: An Efficient SET-Based Approach to Find the Largest Itemset. 316-321 - Sylvie Guillaume:
Discovery of Ordinal Association Rules. 322-327 - Tsau Young Lin, Y. Y. Yao, Eric Louie:
Value Added Association Rules. 328-333 - Ke Wang, Liu Tang, Jiawei Han, Junqiang Liu:
Top Down FP-Growth for Association Rule Mining. 334-340
Semi-structure & Concept Mining
- Tetsuhiro Miyahara, Yusuke Suzuki, Takayoshi Shoudai, Tomoyuki Uchida, Kenichi Takahashi, Hiroaki Ueda:
Discovery of Frequent Tag Tree Patterns in Semistructured Web Documents. 341-355 - Kazuyoshi Furukawa, Tomoyuki Uchida, Kazuya Yamada, Tetsuhiro Miyahara, Takayoshi Shoudai, Yasuaki Nakamura:
Extracting Characteristic Structures among Words in Semistructured Documents. 356-367 - Felix Cheung, Ben Kao, David Wai-Lok Cheung, Chi-Yuen Ng:
An Efficient Algorithm for Incremental Update of Concept Spaces. 368-380
Data Warehouse and Data Cube
- Cuiping Li, Sheng-En Li, Shan Wang, Xiaoyong Du:
Efficient Constraint-Based Exploratory Mining on Large Data Cubes. 381-392 - Don-Lin Yang, Man-Lin Huang, Ming-Chuan Hung:
Efficient Utilization of Materialized Views in a Data Warehouse. 393-404
Bio-Data Mining
- Ning Zhong, Juzhen Dong:
Mining Interesting Rules in Meningitis Data by Cooperatively Using GDT-RS and RSBR. 405-416 - Mukund Deshpande, George Karypis:
Evaluation of Techniques for Classifying Biological Sequences. 417-431 - Vincent Shin-Mu Tseng, Ching-Pin Kao:
Efficiently Mining Gene Expression Data via Integrated Clustering and Validation Techniques. 432-437
Classification (II)
- Yulan Liang, King-Ip Lin, Arpad Kelemen:
Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem. 438-449 - William W. Hsu, Ching-Chi Hsu:
GEC: An Evolutionary Approach for Evolving Classifiers. 450-455 - Hongjian Fan, Kotagiri Ramamohanarao:
An Efficient Single-Scan Algorithm for Mining Essential Jumping Emerging Patterns for Classification. 456-462 - Lili Diao, Keyun Hu, Yuchang Lu, Chunyi Shi:
A Method to Boost Support Vector Machines. 463-468
Temporal Mining
- Xiaoming Jin, Yuchang Lu, Chunyi Shi:
Distribution Discovery: Local Analysis of Temporal Rules. 469-480 - Gabriel Pui Cheong Fung, Jeffrey Xu Yu, Wai Lam:
News Sensitive Stock Trend Prediction. 481-493 - Dit-Yan Yeung, Yuxin Ding:
User Profiling for Intrusion Detection Using Dynamic and Static Behavioral Models. 494-505
Classification (III)
- Lee-Feng Chien, Chien-Kang Huang, Hsin-Chen Chiao, Shih-Jui Lin:
Incremental Extraction of Keyterms for Classifying Multilingual Documents in the Web. 506-516 - Maleq Khan, Qin Ding, William Perrizo:
k-nearest Neighbor Classification on Spatial Data Streams Using P-trees. 517-518 - Jianchao Han, Nick Cercone:
Interactive Construction of Classification Rules. 529-534
Outliers, Missing Data, and Causation
- Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David Wai-Lok Cheung:
Enhancing Effectiveness of Outlier Detections for Low Density Patterns. 535-548 - Yoshikazu Fujikawa, Tu Bao Ho:
Cluster-Based Algorithms for Dealing with Missing Values. 549-554 - Ki Chan, Boon Toh Low, Wai Lam, Kai-Pui Lam:
Extracting Causation Knowledge from Natural Language Texts. 555-560 - Kok-Leong Ong, Wee Keong Ng, Ee-Peng Lim:
Mining Relationship Graphs for Effective Business Objectives. 561-566
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