19,208 research outputs found
On the similarity relation within fuzzy ontology components
Ontology reuse is an important research issue. Ontology
merging, integration, mapping, alignment and versioning
are some of its subprocesses. A considerable research work has
been conducted on them. One common issue to these subprocesses
is the problem of defining similarity relations among ontologies
components. Crisp ontologies become less suitable in all domains
in which the concepts to be represented have vague, uncertain
and imprecise definitions. Fuzzy ontologies are developed to
cope with these aspects. They are equally concerned with the
problem of ontology reuse. Defining similarity relations within
fuzzy context may be realized basing on the linguistic similarity
among ontologies components or may be deduced from their
intentional definitions. The latter approach needs to be dealt
with differently in crisp and fuzzy ontologies. This is the scope
of this paper.ou
Ontology mapping: the state of the art
Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping
Some Issues on Ontology Integration
The word integration has been used with different
meanings in the ontology field. This article
aims at clarifying the meaning of the word âintegrationâ
and presenting some of the relevant work
done in integration. We identify three meanings of
ontology âintegrationâ: when building a new ontology
reusing (by assembling, extending, specializing
or adapting) other ontologies already available;
when building an ontology by merging several
ontologies into a single one that unifies all of
them; when building an application using one or
more ontologies. We discuss the different meanings
of âintegrationâ, identify the main characteristics
of the three different processes and proposethree words to distinguish among those meanings:integration, merge and use
Intelligent multimedia indexing and retrieval through multi-source information extraction and merging
This paper reports work on automated meta-data\ud
creation for multimedia content. The approach results\ud
in the generation of a conceptual index of\ud
the content which may then be searched via semantic\ud
categories instead of keywords. The novelty\ud
of the work is to exploit multiple sources of\ud
information relating to video content (in this case\ud
the rich range of sources covering important sports\ud
events). News, commentaries and web reports covering\ud
international football games in multiple languages\ud
and multiple modalities is analysed and the\ud
resultant data merged. This merging process leads\ud
to increased accuracy relative to individual sources
Knowledge web: realising the semantic web... all the way to knowledge-enhanced multimedia documents
The semantic web and semantic web services are major efforts in order to spread and to integrate knowledge technology to the whole web. The Knowledge Web network of excellence aims at supporting their developments at the best and largest European level and supporting industry in adopting them. It especially investigates the solution of scalability, heterogeneity and dynamics obstacles to the full development of the semantic web. We explain how Knowledge Web results should benefit knowledge-enhanced multimedia applications
A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web
Over the past decade, rapid advances in web technologies, coupled with
innovative models of spatial data collection and consumption, have generated a
robust growth in geo-referenced information, resulting in spatial information
overload. Increasing 'geographic intelligence' in traditional text-based
information retrieval has become a prominent approach to respond to this issue
and to fulfill users' spatial information needs. Numerous efforts in the
Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the
Linking Open Data initiative have converged in a constellation of open
knowledge bases, freely available online. In this article, we survey these open
knowledge bases, focusing on their geospatial dimension. Particular attention
is devoted to the crucial issue of the quality of geo-knowledge bases, as well
as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic
Network, is outlined as our contribution to this area. Research directions in
information integration and Geographic Information Retrieval (GIR) are then
reviewed, with a critical discussion of their current limitations and future
prospects
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