Helping to Develop Knowledge Management Systems by Using a Multi-Agent Approach

2011 ◽  
pp. 348-364
Author(s):  
Aurora Vizcaino ◽  
Juan Pablo Soto ◽  
Javier Portillo ◽  
Mario Piattini
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Computer Science ◽  
Software Agents ◽  
Knowledge Management System ◽  
The Other ◽  
Life Cycle Model ◽  
Technical Aspects ◽  
Retrieval Technique ◽  
Multi Agent

Efforts to develop Knowledge Management have increased in recent years. However, many of the systems implanted in companies are still not greatly used by the employees because the knowledge that these systems have is often not valuable or on other occasions, is useful but employees do not know how to search for that which is most suitable. Moreover, employees often receive too many answers when they consult this kind of systems and they need to waste time evaluating all of them in order to find that which is most suitable for their necessities. On the other hand, many technical aspects should also be considered when developing a multi-agent system 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, first we 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 chapter explains why we consider that software agents are suitable for this end and how they can work in order to reach their goals. Furthermore, a prototype that uses these agents is also described.

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.

scholarly journals Developing a Knowledge Management System for Integrated Vehicle Health Management Using a Data Life Cycle Model

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Alexslis Maindze
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Management System ◽  
Health Management ◽  
Knowledge Management System ◽  
Quality Data ◽  
Life Cycle Model ◽  
Cycle Model ◽  
High Quality Data ◽  
Data Life Cycle

Data forms the foundation on which knowledge is created, captured, used and shared. The lack of an approach consistent with technological changes and needs can facilitate loss of knowledge and increased costs. Integrated Vehicle Health Management (IVHM) is characterized by prognostics and diagnostics which depend heavily on high quality data to perform data-driven, model-based and hybrid computational analysis of asset health. As a result, managing data and knowledge for Integrated Vehicle Health Management (IVHM) requires a data life cycle model that adopts the OSA-CBM data model and integrate with other approaches. This project will propose such a model and use it to support the development of an IVHM knowledge management system.

Digital Technology Advancements in Knowledge Management in Domestic Tour Products in the Russian Federation

2021 ◽  
pp. 135-148
Author(s):  
Vardan Mkrttchian ◽  
Viacheslav Voronin
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Supply Chain ◽  
Life Cycle ◽  
Russian Federation ◽  
Practical Implementation ◽  
Digital Twins ◽  
Software Modules ◽  
Multi Agent ◽  
The Russian Federation

This chapter discusses the capabilities with problem-oriented digital twin avatars, supply chain, volumetric hybrid, and federated-consistent blockchain use to the nature of knowledge. The goal of this chapter is a theoretical study and practical implementation in the form of basic models and software modules and artificial intelligence algorithms in managing the life cycle of an internal Russian tour product. A laboratory for digitization and management, using multi-agent models of intelligent digital twins-avatars, is created. The purpose of these studies is to solve a scientific problem.

Stakeholder performance, corporate social performance

2019 ◽  
Vol 14 (3) ◽  
pp. 242-253
Author(s):  
Jean Biwole Fouda ◽  
Irène Abessolo Abessolo
Keyword(s):  
Life Cycle ◽  
Corporate Social Performance ◽  
Social Performance ◽  
The Other ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Dominant Type ◽  
Content Type ◽  
Essentially Contested Concepts ◽  
Corporate Social

Purpose The purpose of this paper is to find out what added value does the stakeholder performance concept bring with respect to that of corporate social performance. To better understand the developments of these concepts, the authors resort to Gallie’s theory (1956) of essentially contested concepts, the life-cycle model of Hirsch and Levin’s (1999) umbrella concepts. Reconciling these two theoretical frameworks allows us to introduce the competing category notion consisting of a dominant and a dominated-type concepts. Through a historical and synchronic literature examination, CSP is shown to have characteristics of the dominant type, thanks to its more diffuse character. On the other hand, the stakeholder performance would relate to the dominated type, though it provides better operationalization possibilities. Design/methodology/approach To better understand the developments of these concepts, Gallie’s theory (1956) of essentially contested concepts, the life cycle model of Hirsch and Levin’s (1999) umbrella concepts are used. Findings CSP has characteristics of the dominant type, thanks to its more diffuse character. On the other hand, the stakeholder performance relates to the dominated type, though it provides better operationalization. Originality/value CSP as a dominant type and stakeholder performance is a dominated type.

Formal Knowledge Engineering Methods for Knowledge Discovery

2002 ◽  
Vol 01 (02) ◽  
pp. 141-154
Author(s):  
Satheesh Ramachandran
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Life Cycle ◽  
Decision Support ◽  
Knowledge Discovery ◽  
Knowledge Engineering ◽  
The Other ◽  
Full Potential ◽  
Formal Knowledge

This paper presents a framework for the integrated use of formal knowledge engineering methods and data mining based knowledge discovery methods. Knowledge is a key enterprise asset, and organizations are adopting both knowledge engineering and knowledge discovery paradigms for better knowledge management and enhanced decision support capability. Although there exists a useful interdependence between these endeavors, not much effort has been focused on using the full potential of one for the other. This paper presents a framework for the integrated use of established formal knowledge engineering methods and knowledge discovery processes with the ultimate intent of better managing the enterprise knowledge life cycle. It provides a brief overview of the knowledge discovery processes, and introduces a class of formal knowledge engineering methods and the perceived role of these methods in supporting the integration between the two worlds of knowledge discovery and knowledge engineering.

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