Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

INTEGRATING RULE-BASED SYSTEMS AND DATA ANALYTICS TOOLS USING OPEN STANDARD PMML

Published

Author(s)

Yunpeng Li, Utpal Roy, Yung-Tsun Lee, Sudarsan Rachuri

Abstract

Rule-based expert systems such as CLIPS (C Language Integrated Production System) are 1) based on inductive (if-then) rules to elicit domain knowledge and 2) designed to reason new knowledge based on existing knowledge and given inputs. Recently, data mining techniques have been advocated for discovering knowledge from massive historical or real-time sensor data. Combining top-down expert-driven rule models with bottom-up data-driven prediction models facilitates enrichment and improvement of the predefined knowledge in an expert system with data-driven insights. However, combining is possible only if there is a common and formal representation of these models so that they are capable of being exchanged, reused, and orchestrated among different authoring tools. This paper investigates the open standard PMML (Predictive Model Mockup Language) in integrating rule-based expert systems with data analytics tools, so that a decision maker would have access to powerful tools in dealing with both reasoning-intensive tasks and data-intensive tasks. We present a process planning use case in the manufacturing domain, which is originally implemented as a CLIPS-based expert system. Different paradigms in interpreting expert system facts and rules as PMML models (and vice versa), as well as challenges in representing and composing these models, have been explored. They will be discussed in detail.
Proceedings Title
Proceedings of ASME 2015 International Design Engineering Technical Conferences & Computers and
Information in Engineering Conference (IDETC/CIE 2015)
Conference Dates
August 2-5, 2015
Conference Location
Boston, MA, US

Keywords

rule-based system, expert system, predictive model, data analytics, PMML, process planning

Citation

Li, Y. , Roy, U. , Lee, Y. and Rachuri, S. (2015), INTEGRATING RULE-BASED SYSTEMS AND DATA ANALYTICS TOOLS USING OPEN STANDARD PMML, Proceedings of ASME 2015 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2015) , Boston, MA, US (Accessed April 19, 2024)
Created August 2, 2015, Updated October 12, 2021