Results 1 - 10
of
13
C.: A pattern-based framework of change operators for ontology evolution
- On the Move to Meaningful Internet Systems: OTM 2009 Workshops. Volume 5872 of Lecture
"... Abstract. Change operators are the building blocks of ontology evolution. Different layers of change operators have been suggested. In this paper, we present a novel approach to deal with ontology evolution, in particular, change representation as a pattern-based layered operator framework. As a res ..."
Abstract
-
Cited by 13 (8 self)
- Add to MetaCart
(Show Context)
Abstract. Change operators are the building blocks of ontology evolution. Different layers of change operators have been suggested. In this paper, we present a novel approach to deal with ontology evolution, in particular, change representation as a pattern-based layered operator framework. As a result of an empirical study, we identify four different levels of change operators based on the granularity, domain-specificity and abstraction of changes. The first two layers are based on generic structural change operators, whereas the next two layers are domainspecific change patterns. These layers of change patterns capture the real changes in the selected domains. We discuss identification and integration of the different layers.
Evolva: A comprehensive approach to ontology evolution
- In: Proceedings of 6th European Semantic Web Conference (ESWC) PhD Symposium LNCS
, 2009
"... Abstract. Ontology evolution is increasingly gaining momentum in the area of Semantic Web research. Current approaches target the evolution in terms of either content, or change management, without covering both aspects in the same framework. Moreover, they are slowed down as they heavily rely on us ..."
Abstract
-
Cited by 8 (2 self)
- Add to MetaCart
(Show Context)
Abstract. Ontology evolution is increasingly gaining momentum in the area of Semantic Web research. Current approaches target the evolution in terms of either content, or change management, without covering both aspects in the same framework. Moreover, they are slowed down as they heavily rely on user input. We tackle the aforementioned issues by proposing Evolva, a comprehensive ontology evolution framework, which handles a complete ontology evolution cycle, and makes use of background knowledge for decreasing user input. 1 Problem and Methodology Ontologies form the basis of Semantic Web systems. As such, they need to be kept up-to-date for the dependent systems to remain usable. With the increase of complexity and changes occurring in the represented domains, ontology evolution becomes a painstaking and time-consuming process. Thus research has witnessed an increased interest in ontology evolution. We regard ontology evolution as the “timely adaptation of an ontology to the arisen changes and the
What can be done with the Semantic Web? An Overview of Watson-based Applications ⋆
"... Abstract. Thanks to the huge efforts deployed in the community for creating, building and generating semantic information for the Semantic Web, large amounts of machine processable knowledge are now openly available. Watson is an infrastructure component for the Semantic Web, a gateway that provides ..."
Abstract
-
Cited by 3 (0 self)
- Add to MetaCart
(Show Context)
Abstract. Thanks to the huge efforts deployed in the community for creating, building and generating semantic information for the Semantic Web, large amounts of machine processable knowledge are now openly available. Watson is an infrastructure component for the Semantic Web, a gateway that provides the necessary functions to support applications in using the Semantic Web. In this paper, we describe a number of applications relying on Watson, with the purpose of demonstrating what can be achieved with the Semantic Web nowadays and what sort of new, smart and useful features can be derived from the exploitation of this large, distributed and heterogeneous base of semantic information. 1
Ontology Evolution with Evolva
"... Abstract. Ontology evolution is a painstaking and time-consuming process, especially in information rich and dynamic domains. While ontology evolution refers both to the adaptation of ontologies (e.g., through additions or updates possibly discovered from external data sources) and the management of ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Abstract. Ontology evolution is a painstaking and time-consuming process, especially in information rich and dynamic domains. While ontology evolution refers both to the adaptation of ontologies (e.g., through additions or updates possibly discovered from external data sources) and the management of these changes, no existing tools offer both functionalities. The Evolva framework aims to be a blueprint for a comprehensive ontology evolution tool that would cover both tasks. Additionally, Evolva proposes the use of background knowledge sources to reduce user involvement in the ontology adaptation step. This demo focuses on the initial, concrete implementation of our framework. 1
The Methodology, Methods and Tools for Agile Ontology Maintenance – A Status Report
"... Abstract. Ontologies are an appropriate means to represent knowledge ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Abstract. Ontologies are an appropriate means to represent knowledge
Ontology Evolution: A Practical Approach
"... Ontology evolution is increasingly getting research momentum in the Semantic Web field. This is due to the fact that ontologies, forming the backbone of Semantic Web systems, need to be kept up-to-date for ontology-based systems to remain usable. We highlight two research approaches in the domain of ..."
Abstract
- Add to MetaCart
(Show Context)
Ontology evolution is increasingly getting research momentum in the Semantic Web field. This is due to the fact that ontologies, forming the backbone of Semantic Web systems, need to be kept up-to-date for ontology-based systems to remain usable. We highlight two research approaches in the domain of ontology evolution: The first considers the evolution as a pure management of changes performed by the user [7, 9–11], while the second takes into account dynamically updating and learning ontologies without offering extensive change and evolution management functionalities [1, 2, 8]. Many definitions of ontology evolution exist [5]. We understand ontology evolution as the “timely adaptation of an ontology to the arisen changes and the consistent management of these changes ” [6]. This definition indirectly reflects the need of combining the two aforementioned approaches for achieving a successful evolution. Yet no practical and complete solutions exist that cover all stages of evolution. We are planning to close the above gap by proposing a complete ontology evolution framework, Evolva 1 that: firstly covers the entire evolution cycle, and
INTEGRATING SOCIAL WEB WITH SEMANTIC WEB: ONTOLOGY LEARNING AND ONTOLOGY EVOLUTION FROM FOLKSONOMIES
"... In this paper, we present an approach for integrating Social Web with Semantic Web by combining the easiness of annotation of resources in the Social Web and the expressiveness of ontologies to describe the resources in the Semantic Web. Our approach combines ontology learning and ontology evolution ..."
Abstract
- Add to MetaCart
(Show Context)
In this paper, we present an approach for integrating Social Web with Semantic Web by combining the easiness of annotation of resources in the Social Web and the expressiveness of ontologies to describe the resources in the Semantic Web. Our approach combines ontology learning and ontology evolution techniques to provide an integrated Web. Besides, we show how ontology alignment can be used to enrich ontologies in this context. 1
U N I V E R
"... Ontologies can be a powerful tool to structure knowledge and they are a technology which is in the focus of extensive research. Updating the contents of an ontology or improving its interoperability with other ontologies are important but difficult processes [6]. One of the reasons of these difficul ..."
Abstract
- Add to MetaCart
(Show Context)
Ontologies can be a powerful tool to structure knowledge and they are a technology which is in the focus of extensive research. Updating the contents of an ontology or improving its interoperability with other ontologies are important but difficult processes [6]. One of the reasons of these difficulties comes from vague concepts [28], which can cause inconsistencies or problems of interoperability with other ontologies. This work adopts a novel perspective on vagueness that does not focus on capturing the degrees of uncertainty of vague concepts (like previous approaches [22]) but instead models them as flexible concepts capable of evolving and adapting to changes. These changes are usually induced by ontological inconsistencies. Concerning inconsistencies, very little work can be found in the literature that proposes different solutions to solve them rather than removing axioms. In particular, it was not possible to find any work that considered numerical restrictions in the definition of ontological concepts as a possible source of inconsistencies. The work that I am here presenting makes use of the first framework to provide an automatic solution to detect inconsistencies caused by cardinality restrictions and data range restrictions for OWL 2 ontologies [29]. The
Knowledge and Data Engineering Group,
"... Abstract. Providers of products and services are faced with the dual challenge of supporting the languages and individual needs of the global customer while also accommodating the increasing relevance of user-generated content. As a result, the content and localisation industries must now evolve rap ..."
Abstract
- Add to MetaCart
(Show Context)
Abstract. Providers of products and services are faced with the dual challenge of supporting the languages and individual needs of the global customer while also accommodating the increasing relevance of user-generated content. As a result, the content and localisation industries must now evolve rapidly from manually processing predicable content which arrives in large jobs to the highly automated processing of streams of fast moving, heterogeneous and unpredictable content. This requires a new generation of digital content management technologies that combine the agile flow of content from developers to localisers and consumers with the data-driven language technologies needed to handle the volume of content required to feed the demands of global markets. Data-driven technologies such as statistical machine translation, cross-lingual information retrieval, sentiment analysis and automatic speech recognition, all rely on high quality training content, which in turn must be continually harvested based on the human quality judgments made across the end-to-end content processing flow. This paper presents the motivation, approach and initial semantic models of a collection of research demonstrators where they represent a part of, or a step towards, documenting in a semantic model the multi-lingual semantic web.
Evolva: Towards Automatic Ontology Evolution
, 2008
"... Ontologies form the core of Semantic Web systems, and as such, they need to evolve to meet the changing needs of the system and its users. Information is exponentially increasing in organizations’ intranets as well as on the web, especially with the increased popularity of tools facilitating content ..."
Abstract
- Add to MetaCart
Ontologies form the core of Semantic Web systems, and as such, they need to evolve to meet the changing needs of the system and its users. Information is exponentially increasing in organizations’ intranets as well as on the web, especially with the increased popularity of tools facilitating content generation such as wikis, blogs and social software. In such dynamic environments, evolving ontologies should be agile, i.e. with the least knowledge experts ’ input, for reflecting fast changes occurring in repositories, and keeping Semantic Web systems up-to-date. Most of current ontology evolution frameworks mainly rely on user input throughout their evolution process. We propose Evolva, an ontology evolution framework, aiming to substantially reduce or even eliminate user input through exploiting various background knowledge sources. Background knowledge exists in various forms including lexical databases, web pages and Semantic Web ontologies. Evolva has five main components: information discovery, data validation, ontological changes, evolution validation and evolution management. We present in this report an overview of the current work on ontology evolution, followed by our ontology evolution approach and pilot study conducted so far, and we finally conclude with