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A predicate matching algorithm for database rule systems

Published: 01 May 1990 Publication History

Abstract

Forward-chaining rule systems must test each newly asserted fact against a collection of predicates to find those rules that match the fact. Expert system rule engines use a simple combination of hashing and sequential search for this matching. We introduce an algorithm for finding the matching predicates that is more efficient than the standard algorithm when the number of predicates is large. We focus on equality and inequality predicates on totally ordered domains. This algorithm is well-suited for database rule systems, where predicate-testing speed is critical. A key component of the algorithm is the interval binary search tree (IBS-tree). The IBS-tree is designed to allow efficient retrieval of all intervals (e.g. range predicates) that overlap a point, while allowing dynamic insertion and deletion of intervals. The algorithm could also be used to improve the performance of forward-chaining inference engines for large expert systems applications.

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cover image ACM Conferences
SIGMOD '90: Proceedings of the 1990 ACM SIGMOD international conference on Management of data
May 1990
398 pages
ISBN:0897913655
DOI:10.1145/93597
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 May 1990

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SIGMOD 90
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SIGMOD 90: SIGMOD'90
May 23 - 26, 1990
New Jersey, Atlantic City, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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  • (2011)BE-treeProceedings of the 2011 ACM SIGMOD International Conference on Management of data10.1145/1989323.1989390(637-648)Online publication date: 12-Jun-2011
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