scholarly journals A Framework for Automatic Initialization of Multi-Agent Production Systems Using Semantic Web Technologies

2019 ◽  
Vol 4 (4) ◽  
pp. 4330-4337 ◽  
Author(s):  
Felix Ocker ◽  
Ilya Kovalenko ◽  
Kira Barton ◽  
Dawn Tilbury ◽  
Birgit Vogel-Heuser
Keyword(s):  
Semantic Web ◽  
Production Systems ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Automatic Initialization ◽  
Multi Agent

Enhancing Social Networks with Agent and Semantic Web Technologies

2012 ◽  
pp. 83-100 ◽  
Author(s):  
Federico Bergenti ◽  
Enrico Franchi ◽  
Agostino Poggi
Keyword(s):  
Social Networks ◽  
Semantic Web ◽  
Collaborative Work ◽  
Multi Agent Systems ◽  
Semantic Web Technologies ◽  
Agent Based ◽  
Web Technologies ◽  
Agent Systems ◽  
Multi Agent ◽  
Relevant Work

In this chapter, the authors describe the relationships between multi-agent systems, social networks, and the Semantic Web within collaborative work; they also review how the integration of multi-agent systems and Semantic Web technologies and techniques can be used to enhance social networks at all scales. The chapter first provides a review of relevant work on the application of agent-based models and abstractions to the key ingredients of our work: collaborative systems, the Semantic Web, and social networks. Then, the chapter discusses the reasons current multi-agent systems and their foreseen evolution might be a fundamental means for the realization of the future Semantic Social Networks. Finally, some conclusions are drawn.

scholarly journals Combining Semantic Web technologies with Multi-Agent Systems for integrated access to biological resources

2008 ◽  
Vol 41 (5) ◽  
pp. 848-859 ◽  
Author(s):  
Francisco García-Sánchez ◽  
Jesualdo Tomás Fernández-Breis ◽  
Rafael Valencia-García ◽  
Juan Miguel Gómez ◽  
Rodrigo Martínez-Béjar
Keyword(s):  
Semantic Web ◽  
Multi Agent Systems ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Agent Systems ◽  
Biological Resources ◽  
Multi Agent

Resource Allocation for Cloud Computing

2011 ◽  
pp. 90-112 ◽  
Author(s):  
Jorge Ejarque ◽  
Javier Álvarez ◽  
Raül Sirvent ◽  
Rosa M. Badia
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Semantic Web ◽  
Heterogeneous Computing ◽  
New Paradigm ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Computing Paradigm ◽  
Multi Agent ◽  
Semantically Enhanced

Cloud computing has emerged as a distributed computing paradigm where resources are requested on demand and in a very dynamic fashion and paying only for what you consume. This new paradigm created an ecosystem where several providers offer heterogeneous computing resources to satisfy the customers’ computing demand. So, the allocation and adaptation of this demand to the correct resources is a key issue in this ecosystem, because it can produce a mutual benefit for the customers and providers. However, with the wide variety of customers and providers, this allocation is not an easy task. This chapter presents a toolkit that implements a methodology for improving the resource allocation between different Cloud providers. The Semantically Enhanced Resource Allocator (SERA) toolkit introduces the semantic web and multi-agent technologies for facilitating the interoperability between the users and different resource providers. Semantic web technologies provide the required semantic interoperability between the different providers’ vocabularies; meanwhile a platform of configurable agents provides an adaptable and autonomous way of allocating and managing execution requests and resources according to the customers and providers rules.

Using Semantic Web Technologies and Multi-agent System for Multi-dimensional Analysis of Open Health Data

2020 ◽  
Vol 19 (03) ◽  
pp. 2050021
Author(s):  
Salma El Hajjami ◽  
Mohammed Berrada ◽  
Mostafa Harti ◽  
Gayo Diallo
Keyword(s):  
Semantic Web ◽  
Dimensional Analysis ◽  
Health Data ◽  
New Drugs ◽  
Multi Agent Systems ◽  
Semantic Web Technologies ◽  
Daily Lives ◽  
Web Technologies ◽  
Multi Agent ◽  
Source Of Information

Recent years have seen Social Web becoming a global phenomenon, which is being increasingly important in our daily lives. Millions of users are chatting on the Web and social networks and expressing their feelings and opinions about the latest outbreaks, symptoms, illnesses and new drugs. These opinions contain a large amount of data, which are destined to become a major source of information for business intelligence, as they are largely informative and therefore interesting to be dealt with in a decision-making process, in order to evaluate and improve the performance of health system. However, this source of information is currently underutilised. This work describes an approach to creating an analytical health framework that allows the integration and multi-dimensional analysis of available health data, with particular attention to socially generated data, using Semantic Web (SW) technologies and multi-agent systems.

Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė
Keyword(s):  
Semantic Web ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning
Sign in / Sign up

Export Citation Format

Share Document