A guide to expert systems
Building expert systems
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Knowledge acquisition: principles and guidelines
Knowledge acquisition: principles and guidelines
The rise of the expert company
The rise of the expert company
A survey of knowledge acquisition techniques and tools
Knowledge Acquisition
Conceptual models of interactive knowledge acquisition tools
Knowledge Acquisition
Automated generation of model-based knowledge acquisition tools
Automated generation of model-based knowledge acquisition tools
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Knowledge engineering for industrial expert systems
Automatica (Journal of IFAC)
A comparison of text retrieval models
The Computer Journal - Special issue on information retrieval
A user's view of current practice and possibilities
EKAW'92 Proceedings of the 6th European knowledge acquisition workshop on Current developments in knowledge acquisition
The cluster hypothesis revisited
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Explanation-Based Generalization: A Unifying View
Machine Learning
Machine Learning
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Epistheme: a scientific knowledge management environment in the SpeCS collaborative framework
Computers in Industry - Special issue: Knowledge sharing in collaborative design environments
Knowledge acquisition for decision support systems on an electronic assembly line
Expert Systems with Applications: An International Journal
Concept modeling: From origins to multimedia
Multimedia Tools and Applications
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Knowledge acquisition is one of the most important and problematic aspects of developing knowledge-based systems. Many automated tools have been introduced in the past, however, manual techniques are still heavily used. Interviewing is one of the most commonly used manual techniques for a knowledge acquisition process, and few automated support tools exist to help knowledge engineers enhance their performance. This paper presents a knowledge conceptualization tool (KCT) in which the knowledge engineer can effectively retrieve, structure, and formalize knowledge components, so that the resulting knowledge base is accurate and complete. The KCT uses information retrieval technique to facilitate conceptualization, which is one of the human intensive activities of knowledge acquisition. Two information retrieval techniques employing best-match strategies are used: vector space model and probabilistic ranking principle model. A prototype of the KCT was implemented to demonstrate the concept. The results from KCT are compared with the outputs from a manual knowledge acquisition process in terms of amount of information retrieved and the process time spent. An analysis of the results shows that the process time to retrieve knowledge components (e.g., facts, rules, protocols, and uncertainty) of KCT is about half that of the manual process, and the number of knowledge components retrieved from knowledge acquisition activities is four times more than that retrieved through a manual process. Furthermore, KCT captured every knowledge component that the knowledge engineer manually captured. KCT demonstrates the effectiveness of the knowledge acquisition process model proposed in this paper.