Authors:
Martina Freiberg
;
Felix Herrmann
and
Frank Puppe
Affiliation:
University of Würzburg, Germany
Keyword(s):
Knowledge-based System, Clarification KBS, Consultation-Justification Mash Up, KBS UI Design, Agility.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Biomedical Engineering
;
Decision Support Systems
;
Enterprise Software Technologies
;
Expert Systems
;
Health Information Systems
;
Intelligent Problem Solving
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
Regarding knowledge-based systems (KBS), the once common paradigm—perfectly mimicking the abilities of human experts—is gradually replaced by an increasing demand for more (active) user participation. The therefore required key features intelligent data input handling and results presentation/justification, however, are still treated separately most often. In this paper, we propose a novel KBS paradigm, the Clarification KBS, as a mash up type of consultation and justification interaction and presentation—intended to foster active
user participation according to users’ competency; the KBS’ explicability; and support for learnability. We discuss both the theoretical concept of clarification KBS, as well as several distinct variants for realizing appropriate UI- and interaction designs. Further, we report diverse evaluation experiences regarding a specific instantiation of clarification KBS—the ITree KBS type; therefore, we subsume its specific characteristics, describe corresponding c
ase studies, and discuss the respective results.
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