The Application of Basic Principles of Knowledge Engineering in Knowledge Management

2010 ◽  
Vol 108-111 ◽  
pp. 123-128
Author(s):  
Ting Zeng

Knowledge management and knowledge engineering is two important concepts, in recent years. Knowledge Engineering is the engineering solution of the system, emphasizing the process of the acquisition of knowledge and knowledge on behalf of knowledge-based systems in the uncertain process requirements. The purpose of this paper is to discuss how to use the basic principles of knowledge engineering in order to promote knowledge management.

Author(s):  
Meir Russ ◽  
J. Greg Jones ◽  
Jeannette K Jones

Knowledge management strategies and implementation of knowledge-based systems have gained importance over the last decade. However, many organizations are not able to develop “winning” knowledge-based strategies and others waste signifi- cant monies when the knowledge-based systems they invest in fail to produce the desired results. To address the challenges faced by these organizations, a recently developed framework for strategic dilemmas was proposed by Russ, Jones, and Fineman (2006) to aid in the development of knowledge-based (KB) strategies. The framework (C3EEP) identifies six dilemmas that organizations should balance when considering their knowledge management and business strategies. Examples of such dilemmas include the balance between concealment (secrecy) vs. transparency, complementary vs. destroying, and the balance between exploitation and exploration. The framework compliments the six stages in the life cycle of KB systems (KBS) as identified by the academic literature that discusses the development and implementation of KBS from the information systems (IS) perspective (e.g., Lytras, Pouloudi, & Poulymenakou, 2002; Nissen, Kamel, & Sengupta, 2000). This interaction/ linkage between KB strategies and systems is crucial for the success of both. Academic research supports the complex relationship between the two. However, there is no conclusive formula for managing this relationship to achieve success. The purpose of this study will be to identify crossovers between the two streams (strategy and systems) of research by using a systematic literature review. For example, is the academic literature focusing mostly on the learning aspect (late stage in the life cycle) of the exploration strategy while largely ignoring the discussion about attracting the appropriate knowledge (early stage in the life cycle) for this kind of strategy? Or does the academic literature focus on populating a KBS with appropriate complementary knowledge while largely ignoring the dynamics of the transfer of destroying knowledge (learning aspect)? The authors hope to accomplish three goals in this study: (1) to continue the validation of the two (C3EEP and KBS life cycle) frameworks; (2) to identify new research opportunities; and (3) to focus managerial attention on areas of importance in KB strategies and systems that lack depth of academic discussion.


1995 ◽  
Vol 10 (3) ◽  
pp. 269-300 ◽  
Author(s):  
John K. C. Kingston ◽  
Jim G. Doheny ◽  
Ian M. Filby

AbstractThe KADS methodology and its successor, CommonKADS, have gained a reputation for being useful approaches to building knowledge-based systems in a manner which is both systematic and well documented. However, these methods require considerable effort to use them completely. It has been suggested that automated support for KADS or CommonKADS users, in the form of “knowledge engineering workbenches”, could be very useful. These tools would provide computerised assistance to knowledge engineers in organising and representing knowledge, in a similar fashion to the support which CASE tools provide for software engineers. To provide support for KADS or CommonKADS, the workbenches should provide specific support for the modelling techniques recommended by these methods, which are very detailed in the representation and analysis stages of knowledge engineering. A good knowledge engineering workbench should also be easy to use, should be robust and reliable, and should generate output in a presentable format.This paper reports on an evaluation of two commercially available workbenches for supporting the KADS approach: KADS Tool from ILOG and Open KADS Tool from Bull. This evaluation was carried out by AIAI as part of the CATALYST project, funded by the European Community's ESSI programme, which aimed to introduce CommonKADS to two technology-oriented companies. Information is also presented on two other workbenches: the CommonKADS workbench (which will soon become commercially available) and the VITAL workbench. The results show various strengths and weaknesses in each tool.


1994 ◽  
Vol 9 (2) ◽  
pp. 105-146 ◽  
Author(s):  
Dieter Fensel ◽  
Frank van Harmelen

AbstractIn the field of knowledge engineering, dissatisfaction with therapid-prototypingapproach has led to a number of more principled methodologies for the contruction of knowledge-based systems. Instead of immediately implementing the gathered and interpreted knowledge in a given implementation formalism according to the rapid-prototyping approach, many such methodologies centre around the notion of a conceptual model: an abstract, implementation independent description of the relevant problem solving expertise. A conceptual model should describe the task which is solved by the system and the knowledge which is required by it. Although such conceptual models more precisely, and operationally as a means for model evaluation. In this paper, we study a number of such formal and operational languages for specifying conceptual models. To enable a meaningful comparison of such languages, we focus on languages which are all aimed at the same underlying conceptual model, namely that from the KADS method for building KBS. We describe eight formal languages for KADS models of expertise, and compare these languages with respect to their modelling primitives, their semantics, their implementations and their applications, Future research issues in the area of formal and operational specification languages for KBS are identified as the result of studying these languages. The paper also contains an extensive bibliography of research in this area.


Author(s):  
JONATHAN LEE ◽  
JOHN YEN

Several methodologies have been developed to enhance the software life cycle of knowledge-based systems by emphasizing on the use of both prototypes and specifications. However, these methodologies focus on the development phase of knowledge-based systems. The roles of prototypes and specifications in the maintenance phase has not been fully explored. Because a suitable problem specification for a knowledge-based system is often difficult to acquire, validating changes to non-executable solution specification during the maintenance phase can be a problem. To address this, we propose an alternative paradigm in which the prototype complements the specification throughout the life cycle. The traceability between them is facilitated by organizing both types of artifacts using a common functional decomposition structure. Based on our task-based specification methodology (TBSM), we have also developed a knowledge engineering tool (called TAME) to facilitate the acquisition and the organization of the specification and the prototype. The proposed methodology and the tool together can thus enhance the verification, validation, and the maintenance of knowledge-based systems through their life cycles.


Terminology ◽  
2005 ◽  
Vol 11 (1) ◽  
pp. 55-81 ◽  
Author(s):  
Lee Gillam ◽  
Mariam Tariq ◽  
Khurshid Ahmad

This paper discusses a method for corpus-driven ontology design: extracting conceptual hierarchies from arbitrary domain-specific collections of texts. These hierarchies can form the basis for a concept-oriented (onomasiological) terminology collection, and hence may be used as the basis for developing knowledge-based systems using ontology editors. This reference to ontology is explored in the context of collections of terms. The method presented is a hybrid of statistical and linguistic techniques, employing statistical techniques initially to elicit a conceptual hierarchy, which is then augmented through linguistic analysis. The result of such an extraction may be useful in information retrieval, knowledge management, or in the discipline of terminology science itself.


Author(s):  
TIM MENZIES ◽  
KLAUS-DIETER ALTHOFF ◽  
YANNIS KALFOGLOU ◽  
ENRICO MOTTA

At the SEKE'99 conference, knowledge engineering researchers held a panel on the merits of meta-knowledge (i.e. problem solving methods and ontologies) for the development of knowledge-based systems. The original panel was framed as a debate on the merits of meta-knowledge for knowledge maintenance [21]. However, the debate quickly expanded. In the end, we were really discussing the merits of different technologies for the specification of reusable components for KBS. In this brief article we record some of the lively debate from that panel and the email exchanges it generated.


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