By Gerhard Weikum (auth.), Hans-Jörg Schek, Gustavo Alonso, Felix Saltor, Isidro Ramos (eds.)
This booklet constitutes the refereed court cases of the sixth overseas convention on Extending Database know-how, EDBT '98, held in Valencia, Spain, in March 1998. The 32 revised complete papers offered including one invited keynote have been chosen from a complete of 191 submissions. The booklet is split in sections on similarity seek and indexing, question optimization on the internet, Algorithms for info mining, modelling in OLAP, question processing and garage administration, aggregation and precis facts, object-oriented and lively databases, view upkeep and integrity, databases and the net, workflow and medical databases.
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Additional info for Advances in Database Technology — EDBT'98: 6th International Conference on Extending Database Technology Valencia, Spain, March 23–27, 1998 Proceedings
1 Probabilistic Datalog Probabilistic Datalog is an extension of ordinary (two-valued) Datalog (2D). g. 7 indterm(dl,ir). 8 indterm(dl,db). about(D,T) 4-- indterm(D,T). about(D,T) <-- link(D,Dl) , about(Di,T). ql(X) +- about(X, ir) , about(X,db). 5 link(d2,dl). Informally speaking, the probabilistic weight gives the probability that the following predicate is true. 8 about databases (DB). The rule for ql searches for documents dealing with both of these topics. 56 for ql (dl). g. for document d 2 : 0 .
Thus, we have three different types of clauses: 1. Ground facts consist of the head literal only, and all arguments must be constants. Note that 4D supports both positive and negative facts. 2. Rules consist of a head and a body. e. all variables occurring in the head also must occur in the body of the rule. 3. A goal clause consisting of a body only represents a query to the Datalog program to be answered. Declarations allow for specifying closed-world assumptions for predicates. Let q denote a predicate, then q is closed via the declaration #close (q).
Ciaccia, M. Patella, and P. Zezula. M-tree: An efficient access method for similarity search in metric spaces. In Proceedings of the 23rd VLDB International Conference, pages 426-435, Athens, Greece, August 1997. Fag96 R. Fagin. Combining fuzzy information from multiple systems. In Proceedings of the 15th ACM Symposium on Principles of Database Systems, pages 216226, Montreal, Canada, June 1996. FS96 R. Fagin and L. Stockmeyer. Relaxing the triangle inequality in pattern matching. Research Report RJ 10031, IBM, June 1996.