Advances in Database Technologies

Advances in Database Technologies(ADT) is a workshopseries designed to p- mote interaction and discussion among researchers and practitioners in speci?c topics related to advanced data modeling and database technologies. The ?rst ADT workshop was held in conjunction with the 17th International Conference on Conceptual Modeling (ER 98) in Singapore. It consisted of three small wo- shops,i.e.,the InternationalWorkshoponDataWarehousingandDataMining organized by Prof. Sham Navathe and Dr. Mukesh Mohania, the International Workshop on Mobile Data Access organized by Prof. Dik Lun Lee, and the InternationalWorkshopon New DatabaseTechnologiesfor CollaborativeWork Support and Spatio-TemporalData Management organizedby Prof.Yoshifumi Masunaga. These three small workshops were held simultaneously on 19 and 20 November, and the papers were jointly published in this ADT 98 proceedings. Wewouldliketo thankProf.ShamNavathe,Dr. MukeshMohania,Prof.Dik Lun Lee, Prof. Yoshifumi Masunaga and their program committees for wo- ing together to insure an excellent workshop program. The program co-chair of ER 98 Prof. Tok Wang Ling and his organizing committee members gave o- standing support to the workshops with the local arrangements, registration, publicity, and the preparationof the proceedings. Our special thanks go to Prof.

Includes supplementary material: sn.pub/extras

Inhalt
1: Data Warehousing and Data Mining.- A Fuzzy Attribute-Oriented Induction Method for Knowledge Discovery in Relational Databases.- Fast Methods with Magic Sampling for Knowledge Discovery in Deductive Databases with Large Deduction Results.- A Heuristic Method for Correlating Attribute Group Pairs in Data Mining.- Incremental Meta-mining from Large Temporal Data Sets.- On the Suitability of Genetic-Based Algorithms for Data Mining.- Data Visualization in a Web Warehouse.- Recent Advances and Research Problems in Data Warehousing.- Web Warehousing: Design and Issues.- Extending the E/R Model for the Multidimensional Paradigm.- Numerical Aspects in the Data Model of Conceptual Information Systems.- Nested Data Cubes for OLAP.