Article Background for association rules and cost estimate of selected mining algorithms Share on Authors: Jia Liang Han University of Southern, Queensland University of Southern, QueenslandView Profile , Ashley W. Plank University of Southern, Queensland University of Southern, QueenslandView Profile Authors Info & Claims CIKM '96: Proceedings of the fifth international conference on Information and knowledge managementNovember 1996 Pages 73–80https://doi.org/10.1145/238355.238440Online:12 November 1996Publication History 14citation307DownloadsMetricsTotal Citations14Total Downloads307Last 12 Months4Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

A program partition scheme for stratified programs introduced by Apt et al. (1988) is used to study efficient computation of logic programs. We consider three types of program partitions and their corresponding graph representations: 1) the natural partition, 2) stratified partitions, and 3) the reduced partition. The natural (program) partition consists of definitions of relations, each definition being a subprogram. Subprograms of a program partition may consist of several relations. A partition graph is introduced for a program partition, each node of which corresponds to a subprogram. The partition graph for a stratified partition is a directed acyclic graph (DAG). A stratified partition decomposes a program into modules. The stratified partition with the maximum number of modules is the reduced partition. The cost to achieve a reduced partition is linear in the program size, using well known graph algorithms. We introduce the modular interpretations, which are equivalent in semantics to the standard interpretation. The modular interpretations offer encapsulation and may reduce the computation cost for some modules significantly. The modular approach can play an important role in query optimization, efficient termination, programming design, and software engineering. We classify query types and answer types then discuss query optimization for some query types. Many efficient query processing strategies are applicable to restricted subclasses of programs. The program partition method allows us to select the most efficient strategy for each module. For example, if a module is a uniformly bounded recursion, then the module can be terminated efficiently. If a module defines the transitive closure, then efficient program transformations may be applied to this module.

Recursive rules are important to deductive databases. A recursive rule may be compiled into expansions. In this article, the variable-predicate graph (V-P graph) based on the α-graph by loannidis is developed to represent linear recursive function-free rules and their expansions. A naming convention is used for variables and predicates in the V-P graph so that all equivalent recursive rules may map into a unique V-P graph. We propose a graphic construction method (g.c.m.) which derives V-P graphs of expansions directly from the V-P graph of the original rule. This graphic representation reveals some expansion properties not easy to obtain otherwise. We also propose a rule rewriting method in the context of deductive database so that constants, repeated distinguished variables, and/or repeated recursive variables may be removed from recursive rules.