Referencing Resources through Ontology Evolution

Author(s):  
Déliar Rogozan ◽  
Gilbert Paquette

Evolution is a fundamental requirement for useful ontologies. Knowledge evolves continuously in all fields of knowledge due to the progress in research and applications. Because they are theories of knowledge in a precise domain, Ontologies need to evolve because the domain has changed, the viewpoint of the domain has changed or because problems in the original domain conceptualization have to be resolved or have been resolved (Noy & Klein, 2003). Moreover, in open and dynamic environments such as the Semantic Web, the ontologies need to evolve because domain knowledge evolves continually (Heflin & Hendler, 2000) or because ontology-oriented software-agents must respond to changes in users’ needs (Stojanovic, Maedche, Stojanovic, & Studer, 2003).

Author(s):  
Jairo F. de Souza ◽  
Rubens N. Melo ◽  
Jonice Oliveira ◽  
Jano de Souza ◽  
Sean Wolfgand M. Siqueira

To perform tasks on the semantic web, software agents must be able to communicate with other agents using domain ontologies, even when considering different ontologies. In this regard, it is necessary to address semantic interoperability to enable agents to recognize common concepts and misunderstandings. In this paper, the authors propose the use of negotiation concepts in business scenarios for addressing concept compatibilization problems in communication between software agents and present an algorithm developed in the GNoSIS system. A validation of this approach is presented.


Author(s):  
Jairo Francisco de Souza ◽  
Sean W.M. Siqueira ◽  
Rubens N. Melo

In order to perform its tasks on the Semantic Web, software agents must be able to communicate with other agents using domain ontologies, even when considering different ontologies. Thus, it’s necessary to address the semantic interoperability issue to enable agents to recognize common concepts and misunderstandings. This work proposes the use of GNoSIS, a tool for composing ontology similarity functions, and specific modules in Goddard agent architecture in order for software agents to negotiate meanings of terms not defined in its ontology.


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):  
Qazi Mudassar Ilyas

Semantic Web was proposed to make the content machine-understandable by developing ontologies to capture domain knowledge and annotating content with this domain knowledge. Although, the original idea of semantic web was to make content on the World Wide Web machine-understandable, with recent advancements and awareness about these technologies, researchers have applied ontologies in many interesting domains. Many phases in software engineering are dependent on availability of knowledge, and the use of ontologies to capture and process this knowledge is a natural choice. This chapter discusses how ontologies can be used in various stages of the system development life cycle. Ontologies can be used to support requirements engineering phase in identifying and fixing inconsistent, incomplete, and ambiguous requirement. They can also be used to model the requirements and assist in requirements management and validation. During software design and development stages, ontologies can help software engineers in finding suitable components, managing documentation of APIs, and coding support. Ontologies can help in system integration and evolution process by aligning various databases with the help of ontologies capturing knowledge about database schema and aligning them with concepts in ontology. Ontologies can also be used in software maintenance by developing a bug tracking system based upon ontological knowledge of software artifacts and roles of developers involved in software maintenance task.


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.


Author(s):  
Thabet Slimani ◽  
Boutheina Ben Yaghlane ◽  
Khaled Mellouli

Due to the rapidly increasing use of information and communications technology, Semantic Web technology is being increasingly applied in a large spectrum of applications in which domain knowledge is represented by means of an ontology in order to support reasoning performed by a machine. A semantic association (SA) is a set of relationships between two entities in knowledge base represented as graph paths consisting of a sequence of links. Because the number of relationships between entities in a knowledge base might be much greater than the number of entities, it is recommended to develop tools and invent methods to discover new unexpected links and relevant semantic associations in the large store of the preliminary extracted semantic association. Semantic association mining is a rapidly growing field of research, which studies these issues in order to create efficient methods and tools to help us filter the overwhelming flow of information and extract the knowledge that reflect the user need. The authors present, in this work, an approach which allows the extraction of association rules (SWARM: Semantic Web Association Rule Mining) from a structured semantic association store. Then, present a new method which allows the discovery of relevant semantic associations between a preliminary extracted SA and predefined features, specified by user, with the use of Hyperclique Pattern (HP) approach. In addition, the authors present an approach which allows the extraction of hidden entities in knowledge base. The experimental results applied to synthetic and real world data show the benefit of the proposed methods and demonstrate their promising effectiveness.


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.


Author(s):  
Chrisa Tsinaraki

Several consumer electronic devices that allow capturing digital multimedia content (like mp3 recorders, digital cameras, DVD camcorders, smart phones etc.) are available today. These devices have allowed both the amateur and the professional users to produce large volumes of digital multimedia material, which, together with the traditional media objects digitized recently (using scanners, audio and video digitization devices) form a huge distributed multimedia information source. The multimedia material that is available today is usually organized in independent multimedia information sources, developed on top of different software platforms. The Internet, the emergence of advanced network infrastructures that allow for the fast, efficient and reliable transmission of multimedia content and the development of digital multimedia content services on top of them form an open multimedia consumption environment. In this environment, the users access the multimedia material either through computers or through cheap consumer electronic devices that allow the consumption and management of multimedia content. The users of such an open environment need to be able to access the services offered by the different vendors in a transparent way and to be able to compose the different atomic services (like, for example, multimedia content filtering) into new, composite ones. In order to fulfill this requirement, interoperability between the multimedia content services offered is necessary. Interoperability is achieved, at the syntactic level, through the adoption of standards. At the semantic level, interoperability is achieved through the integration of domain knowledge expressed in the form of domain ontologies. An ontology is a logical theory accounting for the intended meaning of a formal vocabulary, i.e. its ontological commitment to a particular conceptualization of the world (Guarino, 1998). The standard that dominates in multimedia content description is the MPEG-7 (Salembier, 2001), formally known as Multimedia Content Description Interface. It supports multimedia content description from several points of view, including media information, creation information, structure, usage information, textual annotations, media semantics, and low-level visual and audio features. Since the MPEG-7 allows the structured description of the multimedia content semantics, rich and accurate semantic descriptions can be created and powerful semantic retrieval and filtering services can be built on top of them. It has been shown, in our previous research (Tsinaraki, Fatourou and Christodoulakis, 2003), that domain ontologies capturing domain knowledge can be expressed using pure MPEG-7 constructs. This way, domain knowledge can be integrated in the MPEG-7 semantic descriptions. The domain knowledge is subsequently utilized for supporting semantic personalization, retrieval and filtering and has been shown to enhance the retrieval precision (Tsinaraki, Polydoros and Christodoulakis, 2007). Although multimedia content description is now standardized through the adoption of the MPEG-7 and semantic multimedia content annotation is possible, multimedia content retrieval and filtering (especially semantic multimedia content retrieval and filtering), which form the basis of the multimedia content services, are far from being successfully standardized.


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.


Sign in / Sign up

Export Citation Format

Share Document