pith. machine review for the scientific record. sign in

arxiv: 1109.0621 · v1 · submitted 2011-09-03 · 💻 cs.AI · cs.SE

Recognition: unknown

Visual Inference Specification Methods for Modularized Rulebases. Overview and Integration Proposal

Authors on Pith no claims yet
classification 💻 cs.AI cs.SE
keywords specificationbpmndroolsflowinferenceintegrationmethodsmodeling
0
0 comments X
read the original 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.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.