Analysis of empirical knowledge acquisition process in optimal design of multi-disciplinary system

The dimensional tolerancing knowledge management system presented in this paper uses Nested Ripple down Rules (NRDR) targeted towards incrementally capturing expert design knowledge. A demonstrated example of such captured knowledge is that which human designers utilize in order to specify dimensional tolerances on shafts and mating holes in order to meet desired classes of fit as set by relevant engineering standards. In doing so, NRDR interface was designed to receive mathematical functions with their specifications prior and during the KA process. This is necessary to be able to exploit relationships among several classes with respect to certain numerical features of the cases in order to accelerate the convergence of the NRDR knowledge acquisition process by generating artificial cases which are likely to trigger the addition of exception rules. The incorporation of equations constitutes a novel contribution to the field of knowledge acquisition with NRDR. The developed dimensional tolerancing knowledge management system would help mechanical designers become more effective in the time-consuming tolerancing process of their designs in the future.

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Strategy maze: an on-line tool for support management of the knowledge acquisition process

Research and Development in Expert Systems IX ◽

10.1017/cbo9780511569944.010 ◽

1993 ◽

pp. 145-164

Author(s):

N. Y. L. Yue ◽

B. Cox

Keyword(s):

Knowledge Acquisition ◽

Acquisition Process ◽

On Line

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Knowledge Geometry

Journal of Information & Knowledge Management ◽

10.1142/s0219649215500288 ◽

2015 ◽

Vol 14 (04) ◽

pp. 1550028 ◽

Cited By ~ 2

Author(s):

Flávio Luis de Mello ◽

Roberto Lins de Carvalho

Keyword(s):

Knowledge Management ◽

Information Processing ◽

Knowledge Acquisition ◽

Information Management ◽

Spatial Representation ◽

Geometric Approach ◽

Alternative Theory ◽

Acquisition Process ◽

Evaluation Systems ◽

Processing Information

This paper aims to present what we call knowledge geometry, an alternative theory for spatial representation of features related to information processing, information management, and knowledge management. It is a unique geometric approach for representing intuition, reification, interpretation, and deduction processes, as well as their relations. We employ the concept of cultural filter and use what we call real, conceptual, and symbolic planes in order to support transformations which occur along the perception of a phenomenon. After that, we discuss the use of evaluation systems to judge concepts and also the use of semantic systems as a communication language. Finally, a framework of the knowledge acquisition process in the field of the proposed theory is offered, proving the feasibility of its automation.

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PRODUCTION-GRAPH: A GRAPH THEORETICAL MODEL FOR CHECKING KNOWLEDGE BASE ANOMALIES

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213092000065 ◽

1992 ◽

Vol 01 (04) ◽

pp. 563-595

Author(s):

ENG LIAN LIM ◽

JOHN McCALLUM ◽

KWOK HUNG CHAN

Keyword(s):

Theoretical Model ◽

Knowledge Acquisition ◽

Knowledge Base ◽

Empirical Knowledge ◽

Distinctive Features ◽

Pathwise Approach ◽

Problem Instances

Knowledge acquisition is tedious and error-prone. Consequently, a knowledge base may be inconsistent, and contains unreachable rules, redundant rules, and rules which may lead to deadends and infinite loops. There are three approaches for checking these anomalies: interactive, non-interactive pairwise and non-interactive pathwise. In this article, we will present a graph theoretical model called Production-graph for checking knowledge base anomalies along the non-interactive pathwise approach. Production-graph uses graph theoretical constructions to represent facts and rules, as well as relevant properties of the knowledge base that leads to anomalies. Distinctive features of Production-graph include: (i) Using Production-graph, we are able to check on groups of problem instances rather than on individual problem instances. This eliminates the problem of having infinitely many problem instances. (ii) Empirical knowledge is used to limit the problem instances to practically realizable problems. (iii) Effects of chaining both rules and facts are considered.

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Validating the Knowledge Acquisition Process Metrics in Content Management Systems

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a1049.1291s319 ◽

2019 ◽

Vol 9 (1S3) ◽

pp. 257-262

Keyword(s):

Knowledge Acquisition ◽

Software Metrics ◽

Knowledge Engineering ◽

Intelligent System ◽

Content Management ◽

Management Systems ◽

Acquisition Process ◽

Mathematical Properties ◽

Process Metrics ◽

Content Management Systems

Measuring the processes involved in knowledge engineering for designing and building an intelligent system has taken significant role. Out of the four basic processes involved in knowledge engineering, this paper deals with the knowledge acquisition process and the metrics necessary for measuring the process itself. Three metrics are proposed for the knowledge acquisition process based on the entailment procedures, its length and complexity, and the cohesion and coupling attributes of the collection of knowledge units. These three metrics are formalized based on the Briand’s mathematical properties for validating software metrics. These metrics are indicative in the way it gives an insight on the design and the development of a knowledgebase. In addition to these metrics, newer metrics can also be proposed for knowledge representation and knowledge sharing processes.

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Conference interpreting and knowledge acquisition

Interpreting ◽

10.1075/intp.00010.cha ◽

2018 ◽

Vol 20 (2) ◽

pp. 204-231 ◽

Cited By ~ 2

Author(s):

Chia-chien Chang ◽

Michelle Min-chia Wu ◽

Tien-chun Gina Kuo

Keyword(s):

Knowledge Acquisition ◽

Target Audience ◽

Language Usage ◽

Specific Knowledge ◽

Acquisition Process ◽

Knowledge Domains ◽

Domain Specific ◽

Analytical Skills ◽

Short Notice ◽

Domain Specific Knowledge

Abstract This paper describes knowledge acquisition of professional conference interpreters in Taiwan when dealing with unfamiliar topics: the focus is on how the required knowledge is developed before, during and after a conference. We interviewed 10 Chinese-English interpreters, to find out about their preparation for such conferences and their approach to developing domain-specific knowledge. We first collected each interpreter’s five latest conference programs and used these to analyze the knowledge domains covered. We then based each interview on one conference agenda, considered representative by the interpreter, to examine the knowledge acquisition process from pre- to post-conference. The results show strategic preparation of unfamiliar topics: to facilitate comprehension and reformulation, interpreters make good use of conference documents and compile glossaries in which they organize the concepts and terminology specific to the conference. As they assimilate the language usage of the presenters and other participants during the conference, they use their analytical skills to manage any difficulties. Keeping in mind the aims of the event (e.g., commercial, scientific), as well as the profiles of the speakers and target audience, helps to optimize availability of relevant knowledge at short notice and continue updating it during the assignment.

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