The Impact of Intelligent Interfaces on the Performance of Knowledge Base Systems

<div><p><em>Although Knowledge is recognized as a strategic force in organizations, knowledge creation and management is not simply the capture and storage of items of information. It requires the storage and processing of associations through which meaning can be derived from the information. Association can be represented in explicit and observable forms in a knowledge base. The paper discusses issues relating to design a better quality</em><em> interactive interface system for human to have a dialog with the knowledge management systems. At the same time, the paper investigates the ease of evaluation and implementation of a knowledge management system. It performs a major role in providing users with capabilities of dealing with underlying systems. Designing a good interface style using knowledge bases can have a profound effect on the nature of the dialog. </em></p><p><em> </em></p><p><em>Interfacing a knowledge base oriented system can be seen as a dialog between the knowledge base and the user. It plays a major role in providing users with capabilities that deal with underlying systems. Designing a good interface style can have a profound effect on the nature of the dialog. Design of a user interface involves determining approaches in which users interact with the knowledge-based system. The design process, can be complex and multifaceted, begins by identifying system users, through classification of them to understanding their characteristics. The study investigates the improvement of performance by performing an actual study of many experimental systems sufficient to provide judgments for taking the right decision. Results confirm that a good interface has a great impact on the performance of knowledge management systems. </em></p></div>

Soft Systems Methodology (SSM) as a Viable Methodology for Knowledge Engineering: A Literature Review

<span>This paper presents a baseline perspective of knowledge engineering (KE) methodologies by taking a critical look at the methodological approaches currently used in knowledge engineering domain. A literature review bordering on; the knowledge role concept, knowledge elicitation techniques, and ontological approaches employed in knowledge engineering for the construction of knowledge-based systems (KBSs) was carried out. Journal and conference articles were sourced from multiple journals and research databases and a multi-step manual cross-checking based on carefully selected extraction and quality criteria were employed. The findings of the study show that the existing methodological approaches employed for constructing KBSs in KE is highly deficient and inefficient for solving KE problems under dynamic and uncertain environments. The paper concludes by presenting a strong argument as to why soft systems methodology is best suited for constructing knowledge base systems (KBS) in a spatially distributed, unstructured and shared domain specific context.</span>

Knowledge Base Systems

A dumb information system in the information supply chain can provide data that is often difficult for the customer to interpret and use. To help in this regard, machine intelligence based on some learning rules is introduced in this chapter. Architecture of the knowledge base and the rule base are explained. The acquired knowledge from the different sources is to be consolidated.