Most enterprises, technology and otherwise, are routinely collecting massive amounts of unstructured information from customer interactions and then attempting to extract knowledge from this information in order to improve core activities such as product development, customer support, and marketing. The knowledge engineering processes for extracting knowledge from this information are often largely manual and extremely inefficient in both cost and time. Therefore, software automation of these manual activities through the creation of highly user-centric Knowledge Engineering Software Products (KESPs) is critical to enabling the rapid and efficient extraction of high-quality knowledge. The primary intent of this paper is to provide a comprehensive theory, including its application and implementation, for developing high-value Knowledge Engineering Software Products. To this end, we have created a representation-based approach to the design and development of KESPs. The theoretical framework of our representational-based approach is the integrated metarepresentational model (IMRM) which provides a natural sequence of representations for guiding the development of complex artifacts such as KESPs. The application of the IMRM to the development of high-value KESPs resulted in the integrated representation-based process methodology (IRPM) which combines, in a rational and structured manner, methods and tools from the technical domains of Knowledge Engineering, Product Design, and Software Engineering. Each domain contributes a distinct set of methods to the IRPM. The knowledge engineering domain provides tools—such as the CommonKADS Agent/Task model—for modeling current work processes that the KESP will automate. The product design domain provides formal tools—such as the House of Quality, Function Structure, Morphological Matrix, and Utility Function—for explicitly defining the user needs for the KESP, and for exploring different design concepts in order to ensure the KESP is high-quality and low-cost. The software engineering domain provides tools—such as Unified Modeling Language (UML) Use Case, Component, and Class diagrams—in order to ensure that a reliable and easy to use KESP is delivered on time and within budget. We have demonstrated the feasibility of the IRPM by implementing it within the context of a real knowledge engineering problem involving the extraction of problem-solution pairs from customer service requests in order to create “smart” products and services. The developed KESP, called the “Service Request Portal” (SRP), used search and content filters to achieve a 30% productivity improvement over the previously manual work process.
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December 2013
Research-Article
A Representation-Based Methodology for Developing High-Value Knowledge Engineering Software Products: Theory, Application, and Implementation
T. Munger
T. Munger
e-mail: tmunger@soe.ucsc.edu
Technology and Information Management,
Baskin School of Engineering,
Technology and Information Management,
Baskin School of Engineering,
University of California
,Santa Cruz, CA 95064
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S. Desa
e-mail: sdesa@soe.ucsc.edu
T. Munger
e-mail: tmunger@soe.ucsc.edu
Technology and Information Management,
Baskin School of Engineering,
Technology and Information Management,
Baskin School of Engineering,
University of California
,Santa Cruz, CA 95064
Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received May 14, 2013; final manuscript received June 5, 2013; published online September 12, 2013. Editor: Bahram Ravani.
J. Comput. Inf. Sci. Eng. Dec 2013, 13(4): 041006 (19 pages)
Published Online: September 12, 2013
Article history
Received:
May 14, 2013
Revision Received:
June 5, 2013
Citation
Desa, S., and Munger, T. (September 12, 2013). "A Representation-Based Methodology for Developing High-Value Knowledge Engineering Software Products: Theory, Application, and Implementation." ASME. J. Comput. Inf. Sci. Eng. December 2013; 13(4): 041006. https://doi.org/10.1115/1.4024914
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