16,190 research outputs found
Algebraic graph transformations for merging ontologies
The conception of an ontology is a complex task influenced by numerous factors like the point of view of the authors or the level of details. Consequently, several ontologies have been developed to model identical or related domains leading to partially overlapping representations. This divergence of conceptualization requires the study of ontologies merging in order to create a common repository of knowledge and integrate various sources of information. In this paper, we propose a formal approach for merging ontologies using typed graph grammars. This method relies on the algebraic approach to graph transformations, SPO (Simple PushOut) which allows a formal representation and ensures the consistence of the results. Furthermore, a new ontologies merging algorithm called GROM (Graph Rewriting for Ontology Merging) is presented
Ontology Merging as Social Choice
The problem of merging several ontologies has important applications in the Semantic Web, medical ontology engineering
and other domains where information from several distinct sources needs to be integrated in a coherent manner.We propose
to view ontology merging as a problem of social choice, i.e. as a problem of aggregating the input of a set of individuals
into an adequate collective decision. That is, we propose to view ontology merging as ontology aggregation. As a first step in
this direction, we formulate several desirable properties for ontology aggregators, we identify the incompatibility of some of
these properties, and we define and analyse several simple aggregation procedures. Our approach is closely related to work
in judgment aggregation, but with the crucial difference that we adopt an open world assumption, by distinguishing between
facts not included in an agentās ontology and facts explicitly negated in an agentās ontology
Ontology construction from online ontologies
One of the main hurdles towards a wide endorsement of ontologies is the high cost of constructing them. Reuse of existing ontologies offers a much cheaper alternative than building new ones from scratch, yet tools to support such reuse are still in their infancy. However, more ontologies are becoming available on the web, and online libraries for storing and indexing ontologies are increasing in number and demand. Search engines have also started to appear, to facilitate search and retrieval of online ontologies. This paper presents a fresh view on constructing ontologies automatically, by identifying, ranking, and merging fragments of online ontologies
A Framework for Semi-automated Web Service Composition in Semantic Web
Number of web services available on Internet and its usage are increasing
very fast. In many cases, one service is not enough to complete the business
requirement; composition of web services is carried out. Autonomous composition
of web services to achieve new functionality is generating considerable
attention in semantic web domain. Development time and effort for new
applications can be reduced with service composition. Various approaches to
carry out automated composition of web services are discussed in literature.
Web service composition using ontologies is one of the effective approaches. In
this paper we demonstrate how the ontology based composition can be made faster
for each customer. We propose a framework to provide precomposed web services
to fulfil user requirements. We detail how ontology merging can be used for
composition which expedites the whole process. We discuss how framework
provides customer specific ontology merging and repository. We also elaborate
on how merging of ontologies is carried out.Comment: 6 pages, 9 figures; CUBE 2013 International Conferenc
Ontology Construction from Online Ontologies
One of the main hurdles towards a wide endorsement of ontologies is the high cost of constructing them. Reuse of existing ontologies offers a much cheaper alternative than building new ones from scratch, yet tools to support such reuse are still in their infancy. However, more ontologies are becoming available on the web, and online libraries for storing and indexing ontologies are increasing in number and demand. Search engines have also started to appear, to facilitate search and retrieval of online ontologies. This paper presents a fresh view on constructing ontologies automatically, by identifying, ranking, and merging fragments of online ontologies
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