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

2016 ◽  
Vol 4 (2) ◽  
pp. 84
Author(s):  
Abid Thyab Al Ajeeli
Keyword(s):  
Knowledge Management ◽  
Knowledge Base ◽  
Knowledge Bases ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Knowledge Based ◽  
Experimental Systems ◽  
Knowledge Base Systems ◽  
The Right ◽  
The Impact

<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>

Ontologies in Expertise Finding Systems

2013 ◽  
pp. 158-177 ◽  
Author(s):  
Maryam Fazel-Zarandi ◽  
Mark S. Fox ◽  
Eric Yu
Keyword(s):  
Knowledge Management ◽  
Requirements Engineering ◽  
Modeling Technique ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Organizational Settings ◽  
Potential Benefits ◽  
The Right ◽  
Expertise Finding ◽  
The Impact

Knowledge Management Systems that enhance and facilitate the process of finding the right expert in an organization have gained much attention in recent years. This chapter explores the potential benefits and challenges of using ontologies for improving existing systems. A modeling technique from requirements engineering is used to evaluate the proposed system and analyze the impact it would have on the goals of the stakeholders. Based on the analysis, an ontology-based expertise finding system is proposed. This chapter also discusses the organizational settings required for the successful deployment of the system in practice.

Use of Knowledge Management Systems and the Impact on the Acquisition of Explicit Knowledge

2008 ◽  
Vol 22 (2) ◽  
pp. 77-101 ◽  
Author(s):  
Holli McCall ◽  
Vicky Arnold ◽  
Steve G. Sutton
Keyword(s):  
Knowledge Management ◽  
Problem Solving ◽  
Knowledge Acquisition ◽  
Reference Materials ◽  
Explicit Knowledge ◽  
Experimental Methodology ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Use Of Knowledge ◽  
The Impact

ABSTRACT: In an era where knowledge is increasingly seen as an organization's most valuable asset, many firms have implemented knowledge-management systems (KMS) in an effort to capture, store, and disseminate knowledge across the firm. Concerns have been raised, however, about the potential dependency of users on KMS and the related potential for decreases in knowledge acquisition and expertise development (Cole 1998; Alavi and Leidner 2001b; O'Leary 2002a). The purpose of this study, which is exploratory in nature, is to investigate whether using KMS embedded with explicit knowledge impacts novice decision makers' judgment performance and knowledge acquisition differently than using traditional reference materials (e.g., manuals, textbooks) to research and solve a problem. An experimental methodology is used to study the relative performance and explicit knowledge acquisition of 188 participants partitioned into two groups using either a KMS or traditional reference materials in problem solving. The study finds that KMS users outperform users of traditional reference materials when they have access to their respective systems/materials, but the users of traditional reference materials outperform KMS users when respective systems/materials are removed. While all users improve interpretive problem solving and encoding of definitions and rules, there are significant differences in knowledge acquisition between the two groups.

Developing and Maintaining Knowledge Management Systems for Dynamic, Complex Domains

2011 ◽  
pp. 203-229 ◽  
Author(s):  
Lisa J. Burnell ◽  
John W. Priest ◽  
John R. Durrett
Keyword(s):  
Knowledge Management ◽  
Business Processes ◽  
Systems Development ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Agent Architectures ◽  
Knowledge Resources ◽  
Knowledge Based ◽  
Development Processes

An effective knowledge-based organization is one that correctly captures, shares, applies and maintains its knowledge resources to achieve its goals. Knowledge Management Systems (KMS) enable such resources and business processes to be automated and are especially important for environments with dynamic and complex domains. This chapter discusses the appropriate tools, methods, architectural issues and development processes for KMS, including the application of Organizational Theory, knowledge-representation methods and agent architectures. Details for systems development of KMS are provided and illustrated with a case study from the domain of university advising.

Developing and Maintaining Knowledge Management Systems for Dynamic, Complex Domains

2011 ◽  
pp. 571-592
Author(s):  
Lisa J. Burnell ◽  
John W. Priest ◽  
John R. Durrett
Keyword(s):  
Knowledge Management ◽  
Business Processes ◽  
Systems Development ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Agent Architectures ◽  
Knowledge Resources ◽  
Knowledge Based ◽  
Development Processes

An effective knowledge-based organization is one that correctly captures, shares, applies and maintains its knowledge resources to achieve its goals. Knowledge Management Systems (KMS) enable such resources and business processes to be automated and are especially important for environments with dynamic and complex domains. This chapter discusses the appropriate tools, methods, architectural issues and development processes for KMS, including the application of Organizational Theory, knowledge-representation methods and agent architectures. Details for systems development of KMS are provided and illustrated with a case study from the domain of university advising.

An Agent System to Manage Knowledge in CoPs

2010 ◽  
pp. 230-248
Author(s):  
Juan Pablo Soto ◽  
Aurora Vizcaíno ◽  
Javier Portillo-Rodríguez ◽  
Mario G. Piattini
Keyword(s):  
Knowledge Management ◽  
Communities Of Practice ◽  
Trust Model ◽  
Knowledge Bases ◽  
Management Systems ◽  
Artificial Agents ◽  
Knowledge Management Systems ◽  
Agent Architecture ◽  
Geographically Distributed ◽  
Multi Agent

This paper proposes a multi-agent architecture and a trust model with which to foster the reuse of information in organizations which use knowledge bases or knowledge management systems. The architecture and the model have been designed with the goal of giving support to communities of practices which are a means of sharing knowledge. However, members of these communities are currently often geographically distributed, and less trust therefore exists among members than in traditional co-localizated communities of practice. This situation has led us to propose our trust model, which can be used to calculate what piece of knowledge is more trustworthy. The architecture’s artificial agents will use this model to recommend the most appropriate knowledge to the community’s members.

E-Cocreation of Knowledge through Informal Communications

2011 ◽  
pp. 135-153
Author(s):  
Kazushi Nishimoto
Keyword(s):  
Knowledge Management ◽  
Knowledge Base ◽  
21St Century ◽  
Knowledge Creation ◽  
Professional Knowledge ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Free Riders ◽  
It Knowledge ◽  
Informal Communications

It is pointed out that the 21st century is an era of knowledge creation where productivity of knowledge is more important than the productivity of things. Therefore, improvement of the productivity of knowledge is an urgent demand from public organizations i.e., industry, academia and government as well as personal individuals. As a method to achieve it, knowledge management systems have recently been studied and developed. However, there have been few cases that could successfully improve the productivity of knowledge; many systems have been installed but not used. One of the principal problems of the ordinary attempts is, I think, the unbalanced way for sharing the knowledge. For example, experts are required to voluntarily provide their professional knowledge to create and to maintain a knowledge-base with many efforts so that novices as free riders can readily exploit the knowledge-base without any efforts. In order to solve and/or to avoid this problem, I focused on informal communications by chance as places for sharing knowledge and my laboratory has been constructed various e-cocreation systems to support sharing and creating knowledge in the informal communications. This chapter introduces some of the research efforts conducted in the author’s laboratory.

Developing Knowledge Management Systems from a Knowledge-Based and Multi-Agent Approach

2009 ◽  
pp. 817-833
Author(s):  
Aurora Vizcaíno ◽  
Juan Pablo Soto ◽  
Javier Portillo-Rodríguez
Keyword(s):  
Knowledge Management ◽  
Software Agents ◽  
Knowledge Flows ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Technical Aspects ◽  
Knowledge Based ◽  
Retrieval Technique ◽  
Multi Agent ◽  
Developing Knowledge

Developing knowledge management systems is a complicated task since it is necessary to take into account how the knowledge is generated, how it can be distributed in order to reuse it, and other aspects related to the knowledge flows. On the other hand, many technical aspects should also be considered such as what knowledge representation or retrieval technique is going to be used. To find a balance between both aspects is important if we want to develop a successful system. However, developers often focus on technical aspects, giving less importance to knowledge issues. In order to avoid this, we have developed a model to help computer science engineers to develop these kinds of systems. In our proposal we first define a knowledge life cycle model that, according to literature and our experience, ponders all the stages that a knowledge management system should give support to. Later, we describe the technology (software agents) that we recommend to support the activities of each stage. The article explains why we consider that software agents are suitable for this end and how they can work in order to reach their goals. Moreover, a prototype that uses these agents is also described.

Physicians' Participation in Practice of Knowledge Management Systems

2013 ◽  
Vol 12 (02) ◽  
pp. 1350012 ◽  
Author(s):  
Hsien-Cheng Lin ◽  
Chen-Wei Yang ◽  
Jeng-Yuan Chiou
Keyword(s):  
Knowledge Management ◽  
Intellectual Capital ◽  
Information Quality ◽  
Management Systems ◽  
Healthcare Organisation ◽  
Knowledge Management Systems ◽  
System Quality ◽  
Is Success ◽  
Knowledge Based ◽  
Patient Health

Healthcare organisations are knowledge-based establishments. At a healthcare organisation, computer-based information systems (ISs) are powerful tools for improving care using decision support such as patient health data recording, storing, delivery and retrieval. This study investigates the physicians' perspective for the success of ISs, and the relationships between the users' satisfactions and intellectual capital. We adopted a questionnaire survey for the purpose of outcome assessment and the correlations among each dimension, from a sample of 181 physicians in Taiwan's international medical service centres. The results indicate that IS success is significantly related to intellectual capital. With regard to IS quality, system quality has no significant effects on information quality and patients' privacy protection. This research provides empirical evidence to evaluate IS success in healthcare organisations and suggestions for how to promote physicians using knowledge management systems.

THE ROLE OF KNOWLEDGE MANAGEMENT SYSTEMS FOR INNOVATION: AN ABSORPTIVE CAPACITY PERSPECTIVE

2013 ◽  
Vol 17 (05) ◽  
pp. 1350019 ◽  
Author(s):  
BERNHARD MOOS ◽  
DANIEL BEIMBORN ◽  
HEINZ-THEO WAGNER ◽  
TIM WEITZEL
Keyword(s):  
Knowledge Management ◽  
Absorptive Capacity ◽  
Manufacturing Firms ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Market Knowledge ◽  
Organisational Knowledge ◽  
Using Data ◽  
The Impact

What is the role of Knowledge Management Systems (KMS) for a firm's innovativeness and absorptive capacity (ACAP)? Research shows that a firm's capacity to acquire and utilise relevant knowledge, i.e., its absorptive capacity, is decisive for innovation success. We develop a theoretical model that links the availability and usage of KMS with a firm's ACAP and its organisational knowledge to explain its contribution for a firm's innovation success. Using data from 222 manufacturing firms, we can show that the availability of a KMS in a firm affects its innovation success by contributing to its ACAP. Looking at the impact of different knowledge types on innovativeness, the results show that only technological knowledge is a substantial determinant of innovation success but not market knowledge.

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