scholarly journals Artificial Intelligence for Knowledge Management

2021 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management

The role of artificial intelligence in knowledge management

2000 ◽  
Vol 13 (5) ◽  
pp. 235-239 ◽  
Author(s):  
E Tsui ◽  
B.J Garner ◽  
S Staab
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management

The Algorithm of Case-Searching Based on AHP Application

2014 ◽  
Vol 513-517 ◽  
pp. 2416-2419
Author(s):  
Cai Xia Wang ◽  
Ning Liu
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Case Management ◽  
Critical Case ◽  
Case Analysis ◽  
Basic Function ◽  
Knowledge Management System ◽  
Teaching Case ◽  
Trained Teachers ◽  
Case Reasoning

The knowledge management system of teaching case corpus adopts case reasoning technology in the field of artificial intelligence. The whole system includes altogether ten modules. They are case uploading, case modification, case analysis, case algorithm and critical case management. The basic function is to assist the trained teachers to get the teaching case knowledge from other teachers, so as to develop teachersspecialty. In the module of case algorithm , in the application of the algorithm of case-searching based on AHP, the case needed by the users can be sorted out in an objective and fair way.

Ontologies and E-Learning

2005 ◽  
pp. 345-356
Author(s):  
Matteo Cristani
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Natural Language Processing ◽  
Knowledge Sharing ◽  
Language Processing ◽  
Information Integration ◽  
Knowledge Engineering ◽  
Formal Ontologies ◽  
E Learning ◽  
Intelligent Information

What is an ontology? Why is this relevant to a learning environment? It is quite well-established in recent investigations on information systems that formal ontologies area crucial problem to deal with, and in fact, received a lot of attention in several different communities, such as knowledge management, knowledge engineering, natural language processing, intelligent information integration, and so on (Fensel, 2000).Ontologies have been developed in artificial intelligence to facilitate knowledge sharing and reuse. The viewpoint we adopt here is taken from the general considerations on the use of philosophical issues in artificial intelligence: “the systematic, formal, axiomatic development of the logic of all forms and modes of being” (Cocchiarella,1991). Another commonly accepted definition is that an ontology is an explicit specification of a shared conceptualization that holds in a particular context.

A Stage Model for NPD Process Maturity and IKMS Implementation

2011 ◽  
pp. 679-697 ◽  
Author(s):  
Nassim Belbaly ◽  
Hind Benbya
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Product Development Process ◽  
Management Systems ◽  
Maturity Stage ◽  
Knowledge Management Systems ◽  
Intelligent Knowledge Management

The objective of this chapter is to provide an analytical tool to assist organizations in their implementations of Intelligent Knowledge Management Systems (IKMS) along the new product development (NPD) process. Indeed, organizations rely on a variety of systems using Artificial Intelligence to support the NPD process that depends on the maturity stage of both the process and type of knowledge managed. Our framework outlines the technological and organizational path that organizations have to follow to integrate and manage knowledge effectively along their new product development process. In doing so, we also address the main limitations of the systems used to date and suggest the evolution towards a new category of KMS based on artificial intelligence that we refer to as Intelligent Knowledge Management Systems. We illustrate our framework with an analysis of several case studies.

Ontologies and E-Learning

2011 ◽  
pp. 322-331 ◽  
Author(s):  
Matteo Cristani
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Natural Language Processing ◽  
Knowledge Sharing ◽  
Language Processing ◽  
Information Integration ◽  
Knowledge Engineering ◽  
Formal Ontologies ◽  
E Learning ◽  
Intelligent Information

What is an ontology? Why is this relevant to a learning environment? It is quite well-established in recent investigations on information systems that formal ontologies area crucial problem to deal with, and in fact, received a lot of attention in several different communities, such as knowledge management, knowledge engineering, natural language processing, intelligent information integration, and so on (Fensel, 2000).Ontologies have been developed in artificial intelligence to facilitate knowledge sharing and reuse. The viewpoint we adopt here is taken from the general considerations on the use of philosophical issues in artificial intelligence: “the systematic, formal, axiomatic development of the logic of all forms and modes of being” (Cocchiarella,1991). Another commonly accepted definition is that an ontology is an explicit specification of a shared conceptualization that holds in a particular context.

Mobile Technology for Knowledge Management

2011 ◽  
pp. 1625-1632
Author(s):  
Volker Derballa ◽  
Key Pousttchi
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Data Warehouse ◽  
Mobile Technology ◽  
Business Processes ◽  
Technological Infrastructure ◽  
It Support ◽  
Mobile Processes ◽  
Design Requirements ◽  
Mobile Context

IT support for knowledge management (KM) is a widely discussed issue. Whereas an overemphasis on technology is often criticized, the general consensus is that a well-balanced combination of technical and social approaches can be a rewarding departure (Alavi & Leidner, 1999). The usage of knowledge management systems (KMSs) (i.e., information systems including for example data warehouse techniques and artificial intelligence tools) is seen as a factor that can beneficially support different KM processes (Frank, 2001; Wiig, 1995). Due to the fact that an increasingly large proportion of work is not conducted in the context of stationary workplaces anymore, it becomes necessary to make KMSs available to those mobile workers (Rao, 2002; Sherman, 1999). Considering the different technological infrastructure in the stationary, as well as the mobile context, a KMS that so far is only available at a stationary workplace cannot simply become mobile without any changes. Further, the aspect of mobility implies specific design requirements for KMS. Taking together the rapid developments in the field of technology, allowing more and more mobile processes to be potentially supported through mobile KMS, as well as the current social and occupational developments, resulting in more mobile workplaces and business processes (Gruhn & Book, 2003), the relevance of mobile KM can be expected to increase in the future.

Artificial Intelligence and Knowledge Management

2021 ◽  
pp. 171-185
Author(s):  
Shabahat Husain ◽  
Jean-Louis Ermine
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management

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.

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