Semantics and Agents Oriented Web Personalization

2016 ◽  
pp. 1018-1032
Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Web Mining ◽  
Information Overload ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Multi Agent Systems ◽  
Web Personalization ◽  
Intelligent Software Agents

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

Semantics and Agents Oriented Web Personalization

2015 ◽  
Vol 6 (2) ◽  
pp. 35-49 ◽  
Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Web Mining ◽  
Information Overload ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Multi Agent Systems ◽  
Web Personalization ◽  
Intelligent Software

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

Intelligent Semantics Approaches for Adaptive Web

2018 ◽  
pp. 201-220
Author(s):  
Anu Sharma ◽  
Aarti Singh
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Web Personalization ◽  
New Era ◽  
Work Done ◽  
The Web

Intelligent semantic approaches (i.e., semantic web and software agents) are very useful technologies for adding meaning to the web. Adaptive web is a new era of web targeting to provide customized and personalized view of contents and services to its users. Integration of these two technologies can further add to reasoning and intelligence in recommendation process. This chapter explores the existing work done in the area of applying intelligent approaches to web personalization and highlighting ample scope for application of intelligent agents in this domain for solving many existing issues like personalized content management, user profile learning, modelling, and adaptive interactions with users.

Web Semantics for Personalized Information Retrieval

2017 ◽  
pp. 166-186 ◽  
Author(s):  
Aarti Singh ◽  
Anu Sharma
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
Web Search ◽  
Information Overload ◽  
Software Agents ◽  
Web Personalization ◽  
Comprehensive Review ◽  
Web Technologies ◽  
Intelligent Interface

This chapter explores the synergy between Semantic Web (SW) technologies and Web Personalization (WP) for demonstrating an intelligent interface for Personalized Information Retrieval (PIR) on web. Benefits of adding semantics to WP through ontologies and Software Agents (SA) has already been realized. These approaches are expected to prove useful in handling the information overload problem encountered in web search. A brief introduction to PIR process is given, followed by description of SW, ontologies and SA. A comprehensive review of existing web technologies for PIR has been presented. Although, a huge contribution by various researchers has been seen and analyzed but still there exist some gap areas where the benefits of these technologies are still to be realized in future personalized web search.

Intelligent Software Agents

2011 ◽  
pp. 155-172
Author(s):  
Stefan Kirn ◽  
Mathias Petsch ◽  
Brian Lees
Keyword(s):  
Intelligent Agents ◽  
New Technology ◽  
Software Agents ◽  
Security Architecture ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Security Issues ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Multi Agent

For a new technology, such as that offered by intelligent agents, to be successful and widely accepted, it is necessary for systems, based on that technology, to be capable of maintaining security and consistency of operation when integrated into the existing infrastructure of an organisation. This paper explores some of the security issues relating to application of intelligent agents and the integration of such systems into existing organisations. First, existing information security issues for enterprises are considered. Then, a short introduction to the new technology of agents and agent systems is given. Following this, the special security problems of the new technology of software agents and the emerging risks for software and enterprises are discussed. Finally, a new security architecture for multi-agent systems is proposed, together with an explanation of how this multilevel architecture can help to improve the security of agent systems.

Web Semantics for Personalized Information Retrieval

2018 ◽  
pp. 795-810
Author(s):  
Aarti Singh ◽  
Anu Sharma
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
Web Search ◽  
Information Overload ◽  
Software Agents ◽  
Web Personalization ◽  
Comprehensive Review ◽  
Web Technologies ◽  
Intelligent Interface

This chapter explores the synergy between Semantic Web (SW) technologies and Web Personalization (WP) for demonstrating an intelligent interface for Personalized Information Retrieval (PIR) on web. Benefits of adding semantics to WP through ontologies and Software Agents (SA) has already been realized. These approaches are expected to prove useful in handling the information overload problem encountered in web search. A brief introduction to PIR process is given, followed by description of SW, ontologies and SA. A comprehensive review of existing web technologies for PIR has been presented. Although, a huge contribution by various researchers has been seen and analyzed but still there exist some gap areas where the benefits of these technologies are still to be realized in future personalized web search.

Mining for Web Personalization

Web Mining ◽  
2011 ◽  
pp. 27-49 ◽  
Author(s):  
Penelope Markellou ◽  
Maria Rigou ◽  
Spiros Sirmakessis
Keyword(s):  
Web Mining ◽  
Information Overload ◽  
Close Relation ◽  
Access To Information ◽  
Web Personalization ◽  
Current Trends ◽  
Technical Issues ◽  
Human Capability ◽  
Scientific Results ◽  
The Web

The Web has become a huge repository of information and keeps growing exponentially under no editorial control, while the human capability to find, read and understand content remains constant. Providing people with access to information is not the problem; the problem is that people with varying needs and preferences navigate through large Web structures, missing the goal of their inquiry. Web personalization is one of the most promising approaches for alleviating this information overload, providing tailored Web experiences. This chapter explores the different faces of personalization, traces back its roots and follows its progress. It describes the modules typically comprising a personalization process, demonstrates its close relation to Web mining, depicts the technical issues that arise, recommends solutions when possible, and discusses the effectiveness of personalization and the related concerns. Moreover, the chapter illustrates current trends in the field suggesting directions that may lead to new scientific results.

Integrating Semantic Web and Software Agents

2012 ◽  
pp. 82-99
Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
Architectural Style ◽  
Bdi Agents ◽  
Agent Programming ◽  
Bdi Agent ◽  
Integration Architecture ◽  
Two Systems ◽  
Interchange Format

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.

Intelligent Agents for E-Learning

2011 ◽  
pp. 25-42
Author(s):  
Ralf Bruns ◽  
Jürgen Dunkel
Keyword(s):  
Web Sites ◽  
Intelligent Agents ◽  
Domain Knowledge ◽  
Multi Agent Systems ◽  
Semantic Web Technologies ◽  
Private Data ◽  
Intelligent Software Agents ◽  
E Learning ◽  
The One ◽  
New Generation

We propose the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in consultancy situations. Intelligent software agents act as clients and advisors using their knowledge in order to assist human users. In the proposed architecture the domain knowledge is semantically modeled by means of XML-based ontology languages such as OWL. Using an inference engine the agents reason on base of their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand private data, which has to be protected against unauthorized access, and on the other hand publicly accessible data spread over different web sites. Comparable to a real consultancy situation, an agent only reveals sensitive private data if it is indispensable for finding a solution. In addition, depending on the actual consultancy situation each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. The usefulness of our approach is proved by the implementation of an advisory system whose objective is to develop virtual student advisers that render support to university students in order to successfully organize und perform their studies.

Integrating Semantic Web and Software Agents

2011 ◽  
Vol 2 (1) ◽  
pp. 60-76 ◽  
Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
Architectural Style ◽  
Bdi Agents ◽  
Agent Programming ◽  
Bdi Agent ◽  
Integration Architecture ◽  
Two Systems ◽  
Interchange Format

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.

Software Agents in Today's Digital Economy

2001 ◽  
pp. 88-100 ◽  
Author(s):  
Mahesh S. Raisinghani
Keyword(s):  
Intelligent Agents ◽  
New Technology ◽  
Software Agents ◽  
Information Filtering ◽  
Intelligent Agent ◽  
Social Dimension ◽  
Economic Changes ◽  
Software Products ◽  
Intelligent Software Agents ◽  
High Level

One of the most discussed topics in the information systems literature today is software agent/intelligent agent technology. Software agents are high-level software abstractions with inherent capabilities for communication, decision making, control, and autonomy. They are programs that perform functions such as information gathering, information filtering, or mediation (running in the background) on behalf of a person or entity. They have several aliases such as agents, bots, chatterbots, databots, intellibots, and intelligent software agents/robots. They provide a powerful mechanism to address complex software engineering problems such as abstraction, encapsulation, modularity, reusability, concurrency, and distributed operations. Much research has been devoted to this topic, and more and more new software products billed as having intelligent agent functionality are being introduced on the market every day. The research that is being done, however, does not wholeheartedly endorse this trend. The current research into intelligent agent software technology can be divided into two main areas: technological and social. The latter area is particularly important since, in the excitement of new and emergent technology, people often forget to examine what impact the new technology will have on people’s lives. In fact, the social dimension of all technology is the driving force and most important consideration of technology itself. This chapter presents a socio-technical perspective on intelligent agents and proposes a framework based on the data lifecycle and knowledge discovery using intelligent agents. One of the key ideas of this chapter is best stated by Peter F. Drucker in Management Challenges for the 21st Century when he suggests that in this period of profound social and economic changes, managers should focus on the meaning of information, not the technology that collects it.

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