Intelligent Semantics Approaches for Adaptive Web

Author(s):  
Anu Sharma ◽  
Aarti Singh

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.

Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey

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.


Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey

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.


Author(s):  
Aarti Singh ◽  
Anu Sharma

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.


2012 ◽  
pp. 82-99
Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen

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.


2011 ◽  
pp. 78-88
Author(s):  
Alexander Mikroyannidis ◽  
Babis Theodoulidis

The rate of growth in the amount of information available in the World Wide Web has not been followed by similar advances in the way this information is organized and exploited. Web adaptation seeks to address this issue by transforming the topology of a Web site to help users in their browsing tasks. In this sense, Web usage mining techniques have been employed for years to study how the Web is used in order to make Web sites more user-friendly. The Semantic Web is an ambitious initiative aiming to transform the Web to a well-organized source of information. In particular, apart from the unstructured information of today’s Web, the Semantic Web will contain machine-processable metadata organized in ontologies. This will enhance the way we search the Web and can even allow for automatic reasoning on Web data with the use of software agents. Semantic Web adaptation brings traditional Web adaptation techniques into the new era of the Semantic Web. The idea is to enable the Semantic Web to be constantly aligned to the users’ preferences. In order to achieve this, Web usage mining and text mining methodologies are employed for the semi-automatic construction and evolution of Web ontologies. This usage-driven evolution of Web ontologies, in parallel with Web topologies evolution, can bring the Semantic Web closer to the users’ expectations.


Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen

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.


Author(s):  
Kevin Curran ◽  
Gary Gumbleton

Tim Berners-Lee, director of the World Wide Web Consortium (W3C), states that, “The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation” (Berners-Lee, 2001). The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents, roaming from page to page, can readily carry out sophisticated tasks for users. The Semantic Web (SW) is a vision of the Web where information is more efficiently linked up in such a way that machines can more easily process it. It is generating interest not just because Tim Berners-Lee is advocating it, but because it aims to solve the problem of information being hidden away in HTML documents, which are easy for humans to get information out of but are difficult for machines to do so. We will discuss the Semantic Web here.


Author(s):  
Nadia Ben Seghir ◽  
Okba Kazar ◽  
Khaled Rezeg ◽  
Samir Bourekkache

Purpose The success of web services involved the adoption of this technology by different service providers through the web, which increased the number of web services, as a result making their discovery a tedious task. The UDDI standard has been proposed for web service publication and discovery. However, it lacks sufficient semantic description in the content of web services, which makes it difficult to find and compose suitable web services during the analysis, search, and matching processes. In addition, few works on semantic web services discovery take into account the user’s profile. The purpose of this paper is to optimize the web services discovery by reducing the search space and increasing the number of relevant services. Design/methodology/approach The authors propose a new approach for the semantic web services discovery based on the mobile agent, user profile and metadata catalog. In the approach, each user can be described by a profile which is represented in two dimensions: personal dimension and preferences dimension. The description of web service is based on two levels: metadata catalog and WSDL. Findings First, the semantic web services discovery reduces the number of relevant services through the application of matching algorithm “semantic match”. The result of this first matching restricts the search space at the level of UDDI registry, which allows the users to have good results for the “functional match”. Second, the use of mobile agents as a communication entity reduces the traffic on the network and the quantity of exchanged information. Finally, the integration of user profile in the service discovery process facilitates the expression of the user needs and makes intelligible the selected service. Originality/value To the best knowledge of the authors, this is the first attempt at implementing the mobile agent technology with the semantic web service technology.


Author(s):  
Krzysztof Juszczyszyn

The World Wide Web (WWW) is a global, ubiquitous, and fundamentally dynamic environment for information exchange and processing. By connecting vast numbers of individuals, the Web enables creation of virtual communities, and during the last 10 years, became a universal collaboration infrastructure. The so-called Semantic Web, a concept proposed by Tim Berners-Lee, is a new WWW architecture that enhances content with formal semantics (Berners-Lee, Hendler, & Lassila, 2001). Hence, the Web content is made suitable for machine processing (i.e., it is described by the associated metadata), as opposed to HTML documents available only for human consumption. Languages such as Resource Description Framework (RDF) and Ontology Web Language (OWL) along with well-known XML are used for description of Web resources. In other words, the Semantic Web is a vision of the future Web in which information is given explicit meaning. This will enable autonomous software agents to reason about Web content and produce intelligent responses to events (Staab, 2002). The ultimate goal of the next generation’s Web is to support the creation of virtual communities which will be composed of software agents and humans cooperating within the same environment. Sharing knowledge within such a community requires a shared conceptual vocabularies—ontologies, which represent the formal common agreement about the meaning of data (Gomez-Perez & Corcho, 2002). Artificial intelligence defines ontologies as explicit, formal specification of a shared conceptualization (Studer, Benjamins, & Fensel, 1998). In this case, a conceptualization stands for an abstract model of some concept from the real world; explicit means that the type of concept used is explicitly defined. Formal refers to the fact that an ontology should be machine readable; and finally shared means that ontology expresses knowledge that is accepted by all the subjects. In short, an ontology defines the terms used to describe and represent an area of knowledge. However, the shared ontologies must be first constructed by using information from many sources which may be of arbitrary quality. Thus, it is necessary to find a way to seamlessly combine the knowledge from many sources, maybe diverse and heterogeneous. The resultant ontologies enable virtual communities and teams to manage and exchange their knowledge. It should be noted, that the word ontology has been used to describe notions with different degrees of structure—from taxonomies (e.g., Yahoo hierarchy), metadata schemes (e.g., Dublin Core), to logical theories. The Semantic Web needs ontologies with a significant degree of structure. These should allow the specification of at least the following kinds of things: • Concepts (which identify the classes of things like cars or birds) from many domains of interest • The relationships that can exist among concepts • The properties (or attributes) those concepts may have


2002 ◽  
Vol 17 (1) ◽  
pp. 87-91 ◽  
Author(s):  
MIKE USCHOLD

In the coming years, the Web is expected to evolve from a structure containing information resources that have little or no explicit semantics to a structure having a rich semantic infrastructure. The key defining feature that is intended to distinguish the future Semantic Web from today's Web is that the content of the Web will be usable by machines (i.e. software agents). Meaning needs to be communicated between agents who advertise and/or require the ability to perform tasks on the Web. Agents also need to determine the meaning of passive (i.e. non-agent) information resources on the web to perform these tasks.


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