Visual Inference Specification Methods for Modularized Rulebases. Overview and Integration Proposal
Krzysztof Kluza, Grzegorz J. Nalepa, {\L}ukasz {\L}ysik
TL;DR
This paper reviews three visual methods for specifying inference in modular rulebases—Drools Flow, BPMN, and XTT2—and proposes integration strategies to overcome their limitations.
Contribution
It introduces an overview of existing visual inference specification methods and proposes integration approaches to enhance their effectiveness in modular rulebases.
Findings
Analyzed limitations of Drools Flow, BPMN, and XTT2.
Proposed integration strategies for these methods.
Enhanced potential for modular rulebase management.
Abstract
The paper concerns selected rule modularization techniques. Three visual methods for inference specification for modularized rule- bases are described: Drools Flow, BPMN and XTT2. Drools Flow is a popular technology for workflow or process modeling, BPMN is an OMG standard for modeling business processes, and XTT2 is a hierarchical tab- ular system specification method. Because of some limitations of these solutions, several proposals of their integration are given.
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Semantic Web and Ontologies · Advanced Database Systems and Queries