MASACAD

2009 ◽  
pp. 1118-1133
Author(s):  
Mohamed Salah Hamdi
Keyword(s):  
Main Idea ◽  
Information Space ◽  
The Internet ◽  
Global Information ◽  
Multi Agent System ◽  
Distributed Knowledge ◽  
Future Evolution ◽  
Multi Agent ◽  
Available Information ◽  
Information Customization

The evolution of the Internet into the Global Information Infrastructure has led to an explosion in the amount of available information. Realizing the vision of distributed knowledge access in this scenario and its future evolution will need tools to customize the information space. In this article we present MASACAD, a multi-agent system that learns to advise students and discuss important problems in relationship to information customization systems and smooth the way for possible solutions. The main idea is to approach information customization using a multi-agent paradigm.

Combating Information Overload by Means of Information Customization Systems

2011 ◽  
pp. 60-92
Author(s):  
Mohamed Salah Hamdi
Keyword(s):  
Artificial Intelligence ◽  
Collaborative Filtering ◽  
Web Mining ◽  
Information Overload ◽  
The Internet ◽  
Global Information ◽  
Intelligent Interfaces ◽  
Information Matching ◽  
Available Information ◽  
Information Customization

The evolution of the Internet into the Global Information Infrastructure has led to an explosion in the amount of available information. The result is the “information overload” of the user, i.e., users have too much information to make a decision or remain informed about a topic. Information customization systems are supposed to be the answer for information overload. They allow users narrowcast what they are looking for and get information matching their needs. Information customization systems are also a bargain of consummate efficiency. The value proposition of such systems is reducing the time spent looking for information. We hold the view that information customization could be best done by combining various artificial intelligence technologies such as collaborative filtering, intelligent interfaces, agents, bots, web mining, and intermediaries. MASACAD, the system described in this chapter, is an example of an information customization system that combines many of the technologies already mentioned and others to approach information customization and combat information overload.

Extracting and Customizing Information Using Multi-Agents

Web Mining ◽  
2011 ◽  
pp. 228-252 ◽  
Author(s):  
Mohamed Salah Hamdi
Keyword(s):  
Main Idea ◽  
Complex Environments ◽  
Time Data ◽  
Client Server ◽  
Windows Nt ◽  
Distributed Object ◽  
Time Space ◽  
Multi Agent ◽  
Information Customization ◽  
Pervasive Access

Rapidly evolving network and computer technology, coupled with the exponential growth of the services and information available on the Internet, has already brought us to the point where hundreds of millions of people should have fast, pervasive access to a phenomenal amount of information, through desktop machines at work, school and home, through televisions, phones, pagers, and car dashboards, from anywhere and everywhere. The challenge of complex environments is therefore obvious: software is expected to do more in more situations, there are a variety of users (Power/Naive, Techie/ Financial/Clerical, ...), there are a variety of systems (Windows/NT/Mac/Unix, Client/Server, Portable, Distributed Object Manager, Web, ...), there are a variety of interactions (Real-time, Data Bases, Other Players, ...), and there are a variety of resources and goals (time, space, bandwidth, cost, security, quality, ...). To cope with such environments, the promise of information customization systems is becoming highly attractive. In this chapter we discuss important problems in relationship to such systems and smooth the way for possible solutions. The main idea is to approach information customization using a multi-agent paradigm.

scholarly journals Implementasi Sistem Load Balancing Menggunakan Metode Least Time First Byte Dan Multi-Agent System Pada Lingkungan Virtual

2019 ◽  
Vol 4 (2) ◽  
pp. 63-70
Author(s):  
Dyah Ayu Wiranti ◽  
Kurnia Siwi Kinasih ◽  
Shinta Rizki Firdina Sugiono
Keyword(s):  
Information System ◽  
Load Balancing ◽  
Response Time ◽  
Service Provider ◽  
The Internet ◽  
Multi Agent System ◽  
Agent System ◽  
Time Value ◽  
Multi Agent ◽  
Modern Era

In this modern era, the technology is growing rapidly, the Internet is misled. This condition will be related to the service provider or commonly referred to as a server. Increasing the number of clients, the server also has to work heavier so that it often occurs overload. The Load Balancing mechanism uses the Least Time First Byte and Multi Agent system methods. This mechanism allows the server to overcome the number of users who perform service requests so that the load from the server can be resolved. This solution is considered efficient and effective because the request process on the information system will be shared evenly on multiple server back ends. The results of the research that can be proved if using this mechanism the server can work well when the request is from a user or client dating, this method successfully distributes the balancer evenly through the server backend. So the server is no longer experiencing overload. This can be proved when a system that has used the load balancing method with 300 connections generates a throughput of 123.1 KB/s as well as response time value of 4.72 MS and a system that does not use the load balancing method has a throughput of 108.4 KB/s as well as a response time value of 120.3 Ms. Therefore by implementing load balancing the performance of the system can always be improved.

An Agent Approach to Manage Heterogeneous and Distributed Knowledge

2020 ◽  
Vol 10 (1) ◽  
pp. 27-48
Author(s):  
Davy Monticolo ◽  
Inaya Lahoud
Keyword(s):  
21St Century ◽  
Information Sources ◽  
Information Network ◽  
Multi Agent System ◽  
Agent System ◽  
Semantic Approach ◽  
Distributed Knowledge ◽  
Technical Report ◽  
Multi Agent ◽  
Heterogeneous Knowledge

Emphasis on knowledge and information is one of the challenges of the 21st century to differentiate the intelligent business enterprises. Enterprises have to develop their organization in order to capture, manage, and use information in a context of continually changing technology. Indeed, knowledge and information are completely distributed in the information network of the company. In addition, knowledge is, by nature, heterogeneous, since it is provided from different information sources like the software, the technical report, the meeting statements, etc. The authors present in this article the architecture of a multi-agent system, which allows the capitalization of the distributed and heterogeneous knowledge. They then present how the agents help business experts to design ontologies in detailing this problem and how the agents extract knowledge from different user databases by using a semantic approach.

Extracting and Customizing Information Using Multi-Agents

2011 ◽  
pp. 1352-1374
Author(s):  
Mohamed Salah Hamdi
Keyword(s):  
Main Idea ◽  
Complex Environments ◽  
Time Data ◽  
Client Server ◽  
Windows Nt ◽  
Distributed Object ◽  
Time Space ◽  
Multi Agent ◽  
Information Customization ◽  
Pervasive Access

Rapidly evolving network and computer technology, coupled with the exponential growth of the services and information available on the Internet, has already brought us to the point where hundreds of millions of people should have fast, pervasive access to a phenomenal amount of information, through desktop machines at work, school and home, through televisions, phones, pagers, and car dashboards, from anywhere and everywhere. The challenge of complex environments is therefore obvious: software is expected to do more in more situations, there are a variety of users (Power/Naive, Techie/ Financial/Clerical, ...), there are a variety of systems (Windows/NT/Mac/Unix, Client/Server, Portable, Distributed Object Manager, Web, ...), there are a variety of interactions (Real-time, Data Bases, Other Players, ...), and there are a variety of resources and goals (time, space, bandwidth, cost, security, quality, ...). To cope with such environments, the promise of information customization systems is becoming highly attractive. In this chapter we discuss important problems in relationship to such systems and smooth the way for possible solutions. The main idea is to approach information customization using a multi-agent paradigm.

A Multi-Agent System for Handling Adaptive E-Services

2010 ◽  
pp. 1346-1351
Author(s):  
Pasquale De Meo ◽  
Giovanni Quattrone ◽  
Giorgio Terracina ◽  
Domenico Ursino
Keyword(s):  
The Internet ◽  
Multi Agent System ◽  
Agent System ◽  
Electronic Service ◽  
E Learning ◽  
Multi Agent ◽  
Software Programs ◽  
Internet Revolution ◽  
Health Applications

An Electronic-Service (E-Service) can be defined as a collection of network-resident software programs that collaborate for supporting users in both accessing and selecting data and services of their interest present in a provider site. Examples of e-services are e-commerce, e-learning, e-government, e-recruitment and e-health applications. E-Services are undoubtely one of the engines presently supporting the Internet Revolution. Indeed, nowadays, a large number and a great variety of providers offer their services also or exclusively via the Internet.

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