Untitled Document

Technical Program of PAKDD-2002

Day 1 (May 6th) : Tutorials and Workshops

Time	Venue	Event
9:00 \| 12:00	Rm 101	[Tutorial 1] "Storage and Retrieval of XML Data using Relational Databases" - Kyuseok Shim and Surajit Chadhuri
	Rm 106	[Tutorial 2] "Data Analytics for Customer Relationship Management" - Jaideep Srivastava
	Rm 107	[Workshop 1] "Knowledge Discovery in Multimedia and Complex Data"
	Rm 105	[Workshop 3] "Toward the Foundation of Data Mining"
	Rm 110	[Workshop 4] "Text Mining"
12:00 \| 14:00	Plum Room + Chinese Dining Room (Lobby) 金梅齋 + 柏壽廳	Lunch
13:30 \| 17:30	Rm 106	[Workshop 2] "Mining Data across Multiple Customer Touchpoints for CRM"
14:00 \| 17:00	Rm 107	[Tutorial 3] "Data Clustering Analysis, from Simple Grouping to Scalable Clustering with Constraints" - Osmar R. Zaiane and Andrew Foss
	Rm 105	[Workshop 3] "Toward the Foundation of Data Mining"
	Rm 110	[Workshop 4] "Text Mining"
18:00 \| 21:00	Sky Lounge (12F) 崑崙廳	Conference Reception

Day 2 (May 7th)

Time	Venue	Event
9:00 \| 9:15		Opening
9:15 \| 10:15	International Reception Hall (1F) 敦睦廳	[Keynote Presentation] "Discovery of Patterns in the Global Climate System using Data Mining" - Prof. Vipin Kumar at University of Minnesota
		Tea break
10:30 \| 12:30	Rm 110	[Session A1] Association Rules (I) 1. Discovering Numeric Association Rules via Evolutionary Algorithm - Jacinto Mata, Jose-Luis Alvarez, and Jose-Cristonal Riquelme 2. Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining - Jochen Hipp, Christoph Mangold, Ulrich Guntzer, and Gholamreza Nakhaeizadeh 3. Association Rule Mining on Remotely Sensed Images Using P-trees - Qin Ding, Qiang Ding, and William Perrizo 4. On the Efficiency of Association-rule Mining Algorithms - Vikram Pudi and Jayant R. Haritsa
	Rm 106	[Session B1] Classification (I) 1. A Function-based Classifier Learning Scheme Using Genetic Programming - Jung-Yi Lin, Been-Chian Chien, and Tzung-Pei Hong 2. SNNB: A Selective Neighborhood based Naive Bayes for Lazy Learning - Zhipeng Xie, Wynne Hsu, Zongtian Liu, and Mong Li Lee 3. A method to Boost Naive Bayesian Classifiers - Lili Diao, Keyun Hu, Yuchang Lu, and Chunyi Shi 4. Toward Bayesian Classifiers with Accurate Probabilities - Charles Ling and Huajie Zhang
	Rm 107	[Session C1] Interestingness 1. Pruning Redundant Association Rules Using Maximum Entropy Principle - Szymon Jaroszewicz and Dan Simovici 2. A Confidence-Lift Support Specification for Interesting Associations Mining - Wen-Yang Lin, Ming-Cheng Tseng, and Ja-Hwung Su 3. Concise Representation of Frequent Patterns based on Generalized Disjunction-free Generators - Marzena Kryszkiewicz and Marcin Gajek 4. Mining Interesting Association Rules: A Data Mining Language* - Show-Jane Yen and Yue-Shi Lee 5. The Lorenz Dominance Order as a Measure of Interestingness in KDD* - Robert J. Hilderman
12:30 \| 14:00	Chi-Lin Pavilion (1F) 麒麟廳	Lunch
14:00 \| 15:30	Rm 110	[Session A2] Sequence Mining 1. Efficient Algorithms for Incremental Update of Frequent Sequences - Minghua Zhang, Ben Kao, David Cheung, and Chi-Lap Yip 2. DELISP: Efficient Discovery of Generalized Sequential Patterns by Delimited Pattern-Growth Technology - Ming-Yen Lin, Suh-Yin Lee, and Sheng-Shun Wang 3. Self-Similarity for Data Mining and Predictive Modeling, A Case Study for Network Data* - Jafar Adib, Wei-Min Shen, and Eaman Noorbakhsh 4. Mining Relationship Graphs for Effective Business objectives* - Kok-Leong Ong, Wee-Keong Ng and Ee-Peng Lim
	Rm 106	[Session B2] Clustering 1. M-FastMap: A Modified FastMap Algorithm for Visual Cluster Validation in Data Mining - Michael Ng and Joshua Huang 2. An Incremental Hierarchical Data Clustering Algorithm Based on Gravity Theory - Chien-Yu Chen, Shien-Ching Hwang, and Yen-Jen Oyang 3. Adding Personality to Information Clustering* - Ah-Hwee Tan and Hong Pan 4. Clustering Large Categorical Data* - Francois-Xavier Jollois and Mohamed Nadif
	Rm 107	[Session C2] Web Mining 1. WebFrame: In Pursuit of Computationally and Cognitively Efficient Web Mining - Tong Zheng, Yonghe Niu, and Randy Goebel 2. Naviz: Website Navigational Behavior Visualizer - Bowo Prasetyo, Iko Pramudiono, Katsumi Takahashi, and Masaru Kitsuregawa 3. Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs* - Zhixiang Chen and Ada Wai-Chee Fu 4. Automatic Information Extraction for Multiple Singular Web Pages* - Chia-Hui Chang, Shih-Chien Kuo, Kuo-Yu Hwang, Chih-Lung Lin, and Tsung-Hsin Ho
15:30 \| 16:00		Tea break
16:00 \| 17:30	Rm 110	[Session A3] Association Rules (II) 1. An Improved Approach for the Discovery of Causal Models via MML - Honghua Dai and Gang Li 2. SETM-MaxK: An Efficient SET-Based Approach to Find the Largest Itemset - Ye-In Chang and Yu-Ming Hsieh 3. Discovery of Ordinal Association Rules* - Sylvie Guillaume 4. Value Added Association Rules* - T.Y. Lin, Y.Y. Yao, and E. Louie 5. Top Down FP-Growth for Association Rule Mining* - Ke Wang, Liu Tang, Jiawei Han, and Junqiang Liu
	Rm 106	[Session B3] Semi-Structure & Concept Mining 1. Discovery of Frequent Tag Tree Patterns in Semistructured Web Documents - T. Miyahara, Y. Suzuki, T. Shoudai, T. Uchida, K. Takahashi, and H. Ueda 2. Extracting Characteristic Structures among Words in Semistructured Documents - K. Furukawa, T. Uchida, K. Yamada, T. Miyahara, T. Shoudai, and Y. Nakamura 3. An Efficient Algorithm for Incremental Update of Concept Space - Felix Cheung, Ben Kao, David Cheung, and C.Y. Ng
	Rm 107	[Session C3] Data Warehouse and Data Cube 1. Efficient Constraint-based Exploratory Mining on Large Data Cubes - Cuiping Li, Shengen Li, Shan Wang, and Xiaoyong Du 2. Efficient Utilization of Materialized Views In a Data Warehouse - Don-Lin Yang, Man-Lin Huang, and Ming-Chuan Hung
18:00 \| 21:00	Evergreen Room (10F) 松柏廳	Banquet

Day 3 (May 8th)

Time	Venue	Event
9:00 \| 10:00	International Reception Hall (1F) 敦睦廳	[Keynote Presentation] "Querying and Mining Data Streams: You Only Get One Look" - Dr. Rajeev Rastogi at Bell Laboratories
10:00 \| 10:15		Tea break
10:15 \| 12:15	International Reception Hall (1F) 敦睦廳	[Invited Plenary Talk] 1. Network Data Mining and Analysis: The NEMESIS Project - Minos Garofalakis and Rajeev Rastogi 2. Privacy Preserving Data Mining: Challenges and Opportunities - Ramakrishnan Srikant 3. A Case for Analytical Customer Relationship Management - Jaideep Srivastava, Ee-Peng Lim, Jau-Hwang Wang, and San-Yih Hwang 4. On Data Clustering Analysis: Scalability, Constraints and Validation - Osmar R. Zaiane, Andrew Foss, Chi-Hoon Lee, and Weinan Wang
12:15 \| 14:00	The Grand Garden Western Restaurant (Lobby) 松鶴廳	Lunch
14:00 \| 15:30	Rm 110	[Session A4] Bio-Data Mining 1. Mining Interesting Rules in Meningitis Data by Cooperatively Using GDT-RS and RSBR - Ning Zhong and Juzhen Dong 2. Evaluation of Techniques for Classifying Biological Sequences - Mukund Deshpande and George Karypis 3. Efficiently Mining Gene Expression Data via Integrated Clustering and Validation Techniques* - Vincent S. M. Tseng and Ching-Pin Kao
	Rm 106	[Session B4] Classification (II) 1. Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem - Yulan Liang, King-Ip Lin, and Arpad Kelemen 2. GEC: An Evolutionary Approach for Evolving Classifiers* - William W. Hsu and Ching-Chi Hsu 3. An Efficient Single-scan Algorithm for Mining Essential Jumping Emerging Patterns for Classification* - Hongjian Fan and Ramamohanarao Kotagiri 4. A Method to Boost Support Vector Machines* - Lili Diao, Keyun Hu, Yuchang Lu, and Chunyi Shi
	Rm 107	[Session C4] Temporal Mining 1. Distribution Discovery: Local Analysis of Temporal Rules - Xiaoming Jin, Yuchang Lu, and Chunyi Shi 2. News Sensitive Stock Trend Prediction - Gabriel Pui Cheong Fung, Jeffrey, Xu Yu and Wai Lam 3. User Profiling for Intrusion Detection Using Dynamic and Static Behavioral Models - Dit-Yan Yeung and Yuxin Ding
15:30 \| 16:00		Tea break
16:00 \| 17:15	Rm 110	[Panel]
	Rm 106	[Session B5] Classification (III) 1. Incremental Extraction of Keyterms for Classifying Multilingual Documents in the Web - Lee-Feng Chien, Chien-Kang Huang, Hsin-Chen Chiao, and Shih-Jui Lin* 2. K-Nearest Neighbor Classification on Spatial Data Streams Using P-Trees - Maleq Khan, Qin Ding, and William Perrizo 3. Interactive Construction of Classification Rules* - Jianchao Han and Nick Cercone
	Rm 107	[Session C5] Outliers, Missing Data and Causation 1. Enhancing Effectiveness of Outlier Detections for Low Density Patterns - Jian Tang, Zhixiang Chen, Ada Wai-chee Fu, and David W. Cheung 2. Scalable Algorithms for Dealing with Missing Values* - Yoshikazu Fujikawa and TuBao Ho 3. Extracting Causation Knowledge from Natural Language Texts* - Ki Chan, Boon-Toh Low, Wai Lam, and Kai-Pui Lam 4. A New Mechanism of Mining Network Behavior* - Shun-Chieh Lin, Shian-Shyong Tseng, and Yao-Tsung Lin
17:15		Adjourn