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A framework and computer system for knowledge-level acquisition, representation, and reasoning with process knowledge
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DOI：10.1016/j.ijhcs.2010.05.004.png)
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Abstract
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The development of knowledge-based systems is usually approached through the combined skills of software and knowledge engineers (SEs and KEs. respectively) and of subject matter experts (SMEs) One of the most critical steps in this task aims at transferring knowledge from SMEs' expertise to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this process is costly and error prone Alleviating such knowledge acqusition bottleneck requires enabling SMEs with the means to produce the target knowledge representations, minimizing the intervention of KEs This is especially difficult in the case of complex knowledge types like processes The analysis of scientific domains like Biology, Chemistry, and Physics uncovers (i) that process knowledge is the single most frequent type of knowledge occurring in such domains and (n) specific solutions need to be devised in order to allow SMEs to represent it in a computational form We present a framework and computer system for the acquisition and representation of process knowledge in scientific domains by SMEs We propose methods and techniques to enable SMEs to acquire process knowledge from the domains, to formally represent it, and to reason about it We have developed an abstract process metamodel and a library of problem solving methods (PSMs), which support these tasks, respectively providing the terminology for SME-tailored process diagrams and an abstract formalization of the strategies needed for reasoning about processes We have implemented this approach as part of the DarkMatter system and formally evaluated it in the context of the intermediate evaluation of Project Halo, an initiative aiming at the creation of question answering systems by SMEs. (C) 2010 Elsevier Ltd All rights reserved
Keywords:
Subject matter experts
Process knowledge
Knowledge acquisition
Knowledge representation
Reasoning
Problem solving methods
Usability
Evaluation
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