The role of frame-based representation in reasoning
Communications of the ACM
On the use of knowledge-based decision support systems in financial management: a survey
Decision Support Systems
The Unified Modeling Language user guide
The Unified Modeling Language user guide
HypEs: an architecture for hypermedia-enabled expert systems
Decision Support Systems
Artificial Intelligence: A Guide to Intelligent Systems
Artificial Intelligence: A Guide to Intelligent Systems
Expert Systems: A View of the Field
IEEE Expert: Intelligent Systems and Their Applications
Using JessTab to Integrate Protégé and Jess
IEEE Intelligent Systems
Web-based expert systems: benefits and challenges
Information and Management
Expert Systems with Applications: An International Journal
Assessing a knowledge-based approach to commercial loan underwriting
Expert Systems with Applications: An International Journal
An integrated and intelligent DSS for manufacturing systems
Expert Systems with Applications: An International Journal
Environmental Modelling & Software
Expert Systems with Applications: An International Journal
A CBR System for Knowing the Relationship between Flexibility and Operations Strategy
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
A fuzzy expert system for business management
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Managing decision knowledge or expertise from domain experts is one of the most exciting challenges in today's knowledge management field. The nature of decision knowledge in determining a firm's financial health is context-dependent, intangible, and tacit in nature. Knowledge-based systems (KBS) have been recognized as a successful paradigm for managing financial decision knowledge attributed to possessing capabilities of reasoning and enhancing the consistency of decision-making. However, most present KBS adopt rules as the knowledge representation scheme, which cannot express the expert's knowledge construct systematically when dealing with more numerous and disordered knowledge connotations. In addition, the standalone nature of the systems hinders them from deploying onto heterogeneous platforms and cannot accommodate to the emerging Web-enabled environment. To reduce these flaws, this study proposes a frame knowledge system in which the structural and procedural decision knowledge is encapsulated so that unnecessary interference can be avoided. A protocol analysis, before encapsulation, is conducted to elicit the tacit and unstructured knowledge from a senior CPA we cooperated with. The deployment and Web enabling issue is tackled by using Jess and Java interoperable computing. With these combined, it is possible to prompt the understandability, accessibility, and reusability of KBS. The effectiveness of the proposed system is validated in supporting the expert's decision-making by conducting an empirical experimentation on 537 companies listed in the Taiwan Stock Exchange Corporation.