Applying Information Gathering Techniques in Business-to-Consumer and Web Scenarios

2009 ◽  
pp. 781-799
Author(s):  
David Camacho
Keyword(s):  
Semantic Web ◽  
Computer Science ◽  
Information Gathering ◽  
Business Community ◽  
Important Research ◽  
Agent Based ◽  
Research Fields ◽  
Multi Agent ◽  
Business To Consumer ◽  
The Web

The last decade has shown the e-business community and computer science researchers that there can be serious problems and pitfalls when e-companies are created. One of the problems is related to the necessity for the management of knowledge (data, information, or other electronic resources) from different companies. This chapter will focus on two important research fields that are currently working to solve this problem — Information Gathering (IG) techniques and Web-enabled Agent technologies. IG techniques are related to the problem of retrieval, extraction and integration of data from different (usually heterogeneous) sources into new forms. Agent and Multi-Agent technologies have been successfully applied in domains such as the Web. This chapter will show, using a specific IG Multi-Agent system called MAPWeb, how information gathering techniques have been successfully combined with agent technologies to build new Web agent-based systems. These systems can be migrated into Business- to-Consumer (B2C) scenarios using several technologies related to the Semantic Web, such as SOAP, UDDI or Web services.

Applying Information Gathering Techniques in Business-to-Consumer and Web Scenarios

2011 ◽  
pp. 91-112
Author(s):  
David Camacho
Keyword(s):  
Computer Science ◽  
Information Gathering ◽  
Business Community ◽  
Multi Agent System ◽  
Important Research ◽  
Agent Based ◽  
Research Fields ◽  
Multi Agent ◽  
Business To Consumer ◽  
The Web

The last decade has shown the e-business community and computer science researchers that there can be serious problems and pitfalls when e-companies are created. One of the problems is related to the necessity for the management of knowledge (data, information, or other electronic resources) from different companies. This chapter will focus on two important research fields that are currently working to solve this problem — Information Gathering (IG) techniques and Web-enabled Agent technologies. IG techniques are related to the problem of retrieval, extraction and integration of data from different (usually heterogeneous) sources into new forms. Agent and Multi-Agent technologies have been successfully applied in domains such as the Web. This chapter will show, using a specific IG Multi-Agent system called MAPWeb, how information gathering techniques have been successfully combined with agent technologies to build new Web agent-based systems. These systems can be migrated into Business-to-

Applying Information Gathering Techniques in Business-to-Consumer and Web Scenarios

2011 ◽  
pp. 1506-1524
Author(s):  
David Camacho
Keyword(s):  
Computer Science ◽  
Information Gathering ◽  
Business Community ◽  
Multi Agent System ◽  
Important Research ◽  
Agent Based ◽  
Research Fields ◽  
Multi Agent ◽  
Business To Consumer ◽  
The Web

The last decade has shown the e-business community and computer science researchers that there can be serious problems and pitfalls when e-companies are created. One of the problems is related to the necessity for the management of knowledge (data, information, or other electronic resources) from different companies. This chapter will focus on two important research fields that are currently working to solve this problem — Information Gathering (IG) techniques and Web-enabled Agent technologies. IG techniques are related to the problem of retrieval, extraction and integration of data from different (usually heterogeneous) sources into new forms. Agent and Multi-Agent technologies have been successfully applied in domains such as the Web. This chapter will show, using a specific IG Multi-Agent system called MAPWeb, how information gathering techniques have been successfully combined with agent technologies to build new Web agent-based systems. These systems can be migrated into Business-to-

AGENT-BASED SYSTEM ARCHITECTURE FOR DYNAMIC AND OPEN ENVIRONMENTS

2003 ◽  
Vol 02 (01) ◽  
pp. 105-133 ◽  
Author(s):  
ELHADI SHAKSHUKI ◽  
HAMADA GHENNIWA ◽  
MAHAMED KAMEL
Keyword(s):  
System Architecture ◽  
Rapid Growth ◽  
Dynamic Environment ◽  
Information Gathering ◽  
Information Resources ◽  
Architecture Design ◽  
Agent Based ◽  
Interface Agents ◽  
Multi Agent ◽  
Computing Environments

The rapid growth of the network-centered (Internet and Intranet) computing environments requires new architectures for information gathering systems. Typically, in these environments, the information resources are dynamic, heterogeneous and distributed. In addition, these computing environments are open, where information resources may be connected or disconnected at any time. This paper presents an architecture for a multi-agent information gathering system. The architecture includes three types of agents: interface, broker and resource agents. The interface agents interact with the users to fulfill their interests and preferences. The resource agents access and capture the content of the information resources. The broker agents facilitate cooperation among the information and the resource agents to achieve their desired goals. This paper provides the agents' architecture, design and implementations that enable them to cooperate, coordinate and communicate with each other to gather information in an open and dynamic environment.

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.

How Can We Trust Agents in Multi-Agent Environments? Techniques and Challenges

2009 ◽  
pp. 2843-2864 ◽  
Author(s):  
Kostas Kolomvatsos ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Computer Science ◽  
Research Area ◽  
Software Components ◽  
Important Research ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Potential Partner ◽  
Multi Agent ◽  
Important Research Area

The field of Multi-agent systems (MAS) has been an active area for many years due to the importance that agents have to many disciplines of research in computer science. MAS are open and dynamic systems where a number of autonomous software components, called agents, communicate and cooperate in order to achieve their goals. In such systems, trust plays an important role. There must be a way for an agent to make sure that it can trust another entity, which is a potential partner. Without trust, agents cannot cooperate effectively and without cooperation they cannot fulfill their goals. Many times, trust is based on reputation. It is an indication that we may trust someone. This important research area is investigated in this book chapter. We discuss main issues concerning reputation and trust in MAS. We present research efforts and give formalizations useful for understanding the two concepts.

The Geospatial Semantic Web

2011 ◽  
pp. 588-609 ◽  
Author(s):  
Rafael Moreno-Sanchez
Keyword(s):  
Semantic Web ◽  
Research And Development ◽  
Computer Science ◽  
Geospatial Data ◽  
Future Research ◽  
Science Students ◽  
Geospatial Information ◽  
Information Professionals ◽  
The Web ◽  
The Way

The Semantic Web (SW) and Geospatial Semantic Web (GSW) are considered the next step in the evolution of the Web. For most non-Web specialists, geospatial information professionals, and non-computer-science students these concepts and their impacts on the way we use the Web are not clearly understood. The purpose of this chapter is to provide this broad audience of non-specialists with a basic understanding of: the needs and visions driving the evolution toward the SW and GSW; the principles and technologies involved in their implementation; the state of the art in the efforts to create the GSW; the impacts of the GSW on the way we use the Web to discover, evaluate, and integrate geospatial data and services; and the needs for future research and development to make the GSW a reality. A background on the SW is first presented to serve as a basis for more specific discussions on the GSW.

scholarly journals A multi-agent based system with big data processing for enhanced supply chain agility

2016 ◽  
Vol 29 (5) ◽  
pp. 706-727 ◽  
Author(s):  
Mihalis Giannakis ◽  
Michalis Louis
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Semantic Web ◽  
Supply Chains ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Agent Systems ◽  
Supply Chain Agility ◽  
Multi Agent

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

scholarly journals Can models of agents be transferred between different areas?

2000 ◽  
Vol 15 (2) ◽  
pp. 197-203 ◽  
Author(s):  
RUTH AYLETT ◽  
KERSTIN DAUTENHAHN ◽  
JIM DORAN ◽  
MICHAEL LUCK ◽  
SCOTT MOSS ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Multi Agent Systems ◽  
Ongoing Research ◽  
Agent Based ◽  
Agent Systems ◽  
Sustained Activity ◽  
Diverse Environment ◽  
The World ◽  
Multi Agent

One of the main reasons for the sustained activity and interest in the field of agent-based systems, apart from the obvious recognition of its value as a natural and intuitive way of understanding the world, is its reach into very many different and distinct fields of investigation. Indeed, the notions of agents and multi-agent systems are relevant to fields ranging from economics to robotics, in contributing to the foundations of the field, being influenced by ongoing research, and in providing many domains of application. While these various disciplines constitute a rich and diverse environment for agent research, the way in which they may have been linked by it is a much less considered issue. The purpose of this panel was to examine just this concern, in the relationships between different areas that have resulted from agent research. Informed by the experience of the participants in the areas of robotics, social simulation, economics, computer science and artificial intelligence, the discussion was lively and sometimes heated.

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