A formal methodology for acquiring and representing expert knowledge
Nancy Cooke, James E. McDonald
Abstract
Nancy Cooke, James E. McDonald
Abstract
The process of eliciting knowledge from human experts and representing that knowledge in an expert or knowledge-based system suffers from numerous problems. Not only is this process time-consuming and tedious, but the weak knowledge acquisition methods typically used (i.e., interviews and protocol analysis) are inadequate for eliciting tacit knowledge and may, in fact, lead to inaccuracies in the knowledge base. In addition, the intended knowledge representation scheme guides the acquisition of knowledge resulting in a representation-driven knowledge base as opposed to one that is knowledge-driven. In this paper, a formal methodology is proposed that employs techniques from the field of cognitive psychology to uncover expert knowledge as well as an appropriate representation of that knowledge. The advantages of such a methodology are discussed, as well as results from studies concerning the elicitation of concepts from experts and the assignment of labels to links in empirically derived semantic networks.
OpenAlex reports 74 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The process of eliciting knowledge from human experts and representing that knowledge in an expert or knowledge-based system suffers from numerous problems. Not only is this process time-consuming and tedious, but the weak knowledge acquisition methods typically used (i.e., interviews and protocol analysis) are inadequate for eliciting tacit knowledge and may, in fact, lead to inaccuracies in the knowledge base. In addition, the intended knowledge representation scheme guides the acquisition of knowledge resulting in a representation-driven knowledge base as opposed to one that is knowledge-driven. In this paper, a formal methodology is proposed that employs techniques from the field of cognitive psychology to uncover expert knowledge as well as an appropriate representation of that knowledge. The advantages of such a methodology are discussed, as well as results from studies concerning the elicitation of concepts from experts and the assignment of labels to links in empirically derived semantic networks.
Key concepts: Computer science, Knowledge base, Knowledge representation and reasoning, Knowledge acquisition, Tacit knowledge, Body of knowledge, Procedural knowledge, Knowledge management