Date: Fri, 12 Mar 99 12:00:42 JST From: pakdd99@ai.csse.yamaguchi-u.ac.jp Subject: Call for Participation (PAKDD-99) The Third Pacific-Asia Conference on Knowledge Discovery and Data Mining Xiangshan Hotel, Beijing, China April 26-28, 1999 C A L L F O R P A R T I C I P A T I O N Home Page: http://ain2.ai.csse.yamaguchi-u.ac.jp/pakdd99 PAKDD-99 provides an international forum for the sharing of original research results and practical development experiences among researchers and application developers from different KDD related areas such as machine learning, databases, statistics, knowledge acquisition, data visualization, knowledge-based systems, soft computing, and high performance computing. It follows the success of PAKDD-97 held in Singapore in 1997 and PAKDD-98 held in Australia in 1998 by bringing together participants from universities, industry and government. PAKDD-99 encourages both new theory/methodologies and real world applications, and covers broad and diverse topics in data mining and knowledge discovery. The technical sessions include: Association Rules Mining; Feature Selection and Generation; Mining in Semi, Un-structured Data; Interestingness, Surprisingness, and Exceptions; Rough Sets, Fuzzy Logic, and Neural Networks; Induction, Classification, and Clustering; Causal Model and Graph-Based Methods; Visualization; Agent-Based, and Distributed Data Mining; Advanced Topics and New Methodologies. Of the 158 submissions, we accepted 29 regular papers and 37 short papers for presentation at the conference and for publication in the conference proccedings by Springer-Verlag as a book, titled `Methodologies for Knowledge Discovery and Data Mining' (Lecture Notes in Artificial Intelligence 1574). In addition, over 20 papers were accepted for poster presentation. The PAKDD-99 program is further supplemented by two invited speakers: Won Kim and Hiroshi Motoda, a special session on Emerging KDD Technology (Speakers: Zdzislaw Pawlak, Philip Yu, T.Y. Lin, Hiroshi Tsukimoto), and a panel session on Knowledge Management in Data Mining (Chair: Xindong Wu; Panelists: Rao Kotagiri, Zhongzhi Shi, Jan M. Zytkow). Two tutorials: Automated Discovery - Combining AI, Statistics and Theory of Knowledge by Jan M. Zytkow, Quality Data and Effective Mining by Hongjun Lu, and a workshop on Knowledge Discovery from Advanced Databases organized by Mohamed Quafafou and Philip Yu, are also offered to all conference participants on April 26.
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