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An Analysis of Knowledge Acquisition Roles and Participants
Author(s) -
Wagner William P.,
Holsapple Clyde W.
Publication year - 1997
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/1468-0394.00036
Subject(s) - variety (cybernetics) , computer science , knowledge acquisition , process (computing) , field (mathematics) , knowledge management , domain knowledge , data science , domain (mathematical analysis) , body of knowledge , human–computer interaction , artificial intelligence , mathematical analysis , mathematics , pure mathematics , operating system
Much recent research effort in the field of knowledge acquisition (KA) has focussed on extending knowledge acquisition techniques and processes to include a wider array of participants and knowledge sources in a variety of knowledge acquisition scenarios. As the domain of expert systems applications and research has expanded, techniques have been developed to acquire and incorporate knowledge from groups of experts and from various sources such as text, video, and audio tapes. However, the dominant participant‐role model remains that of the knowledge engineer eliciting knowledge from one or more human experts. This conceptual gap has contributed to the major divisions in the KA field between researchers interested in manual KA and those developing tools for automated KA. This article considers the wide variety of possible KA scenarios and presents a meta‐view of KA participants and the roles they may assume.We suggest that it is more appropriate to think of knowledge acquisition participants as playing one or more roles. These include knowledge sources, agents and targets for KA processes. We also present a participant model drawn from research in decision support systems that more accurately characterizes the diversity of the entities participating in the KA process. This view is more inclusive as it allows us to consider both human‐human and human‐computer KA interactions as well as the whole variety of knowledge sources and targets. A careful consideration of the meta‐view and its associated role‐participant mappings also yields the new ideas of the elemental and composite role and the multi‐role entity. These new constructs are then used to identify areas where research is currently needed and to generate specific research issues. Taken altogether, this view allows a more flexible consideration of the many possible combinations that can and frequently do occur in actual KA situations.

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