3,151 research outputs found
Building a terminology network for search: the KoMoHe project
The paper reports about results on the GESIS-IZ project "Competence Center
Modeling and Treatment of Semantic Heterogeneity" (KoMoHe). KoMoHe supervised a
terminology mapping effort, in which 'cross-concordances' between major
controlled vocabularies were organized, created and managed. In this paper we
describe the establishment and implementation of cross-concordances for search
in a digital library (DL).Comment: 5 pages, 2 figure, Dublin Core Conference 200
Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review
Since the Simple Knowledge Organization System (SKOS) specification and its
SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a
significant number of conventional knowledge organization systems (KOS)
(including thesauri, classification schemes, name authorities, and lists of
codes and terms, produced before the arrival of the ontology-wave) have made
their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS"
as an umbrella term to refer to all of the value vocabularies and lightweight
ontologies within the Semantic Web framework. The paper provides an overview of
what the LOD KOS movement has brought to various communities and users. These
are not limited to the colonies of the value vocabulary constructors and
providers, nor the catalogers and indexers who have a long history of applying
the vocabularies to their products. The LOD dataset producers and LOD service
providers, the information architects and interface designers, and researchers
in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper
examines a set of the collected cases (experimental or in real applications)
and aims to find the usages of LOD KOS in order to share the practices and
ideas among communities and users. Through the viewpoints of a number of
different user groups, the functions of LOD KOS are examined from multiple
dimensions. This paper focuses on the LOD dataset producers, vocabulary
producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on
Digital Librarie
Comparing human and automatic thesaurus mapping approaches in the agricultural domain
Knowledge organization systems (KOS), like thesauri and other controlled
vocabularies, are used to provide subject access to information systems across
the web. Due to the heterogeneity of these systems, mapping between
vocabularies becomes crucial for retrieving relevant information. However,
mapping thesauri is a laborious task, and thus big efforts are being made to
automate the mapping process. This paper examines two mapping approaches
involving the agricultural thesaurus AGROVOC, one machine-created and one human
created. We are addressing the basic question "What are the pros and cons of
human and automatic mapping and how can they complement each other?" By
pointing out the difficulties in specific cases or groups of cases and grouping
the sample into simple and difficult types of mappings, we show the limitations
of current automatic methods and come up with some basic recommendations on
what approach to use when.Comment: 10 pages, Int'l Conf. on Dublin Core and Metadata Applications 200
Ontology mapping by concept similarity
This paper presents an approach to the problem of mapping ontologies. The motivation for the research stems from the Diogene Project which is developing a web training environment for ICT professionals. The system includes high quality training material from registered content providers, and free web material will also be made available through the project's "Web Discovery" component. This involves using web search engines to locate relevant material, and mapping the ontology at the core of the Diogene system to other ontologies that exist on the Semantic Web. The project's approach to ontology mapping is presented, and an evaluation of this method is described
Interoperable subject retrieval in a distributed multi-scheme environment : new developments in the HILT project
The HILT (HIgh-Level Thesaurus) project (http://hilt.cdlr.strath.ac.uk/), based primarily at the Centre for Digital Library Research (CDLR) (http://cdlr.strath.ac.uk/) at Strathclyde University in Glasgow is entering its fourth stage following the completion of Phases I (http://hilt.cdlr.strath.ac.uk/index1.html) and II (http://hilt.cdlr.strath.ac.uk/index2.html) and the Machine to Machine (M2M) Feasibility Study (http://hilt.cdlr.strath.ac.uk/hiltm2mfs/). HILT is funded by the Joint Information Systems Committee (JISC) in the United Kingdom (UK) to examine an issue of global significance - facilitating interoperability of subject descriptions in a distributed, cross-service retrieval environment where different services use different subject and classification schemes to describe content, making cross-searching by subject difficult. HILT Phase I determined that there was a community consensus in the UK in favour of using inter-scheme mapping to achieve interoperability between services using different schemes, an approach followed by several recent projects (Heery et al, 2001; Koch et al, 2001; MACS, 2005; Saeed and Chaudhury 2002). HILT Phase II chose a spine-based approach to mapping and chose the Dewey Decimal Classification (DDC) as the central scheme to which all other schemes would be mapped. It also built an illustrative pilot mapping service, based on an adaptation of the Wordmap (http://www.wordmap.com/) terminology-handling software and made a range of recommendations on issues requiring further research and ongoing development requirements
A Pattern Based Approach for Re-engineering Non-Ontological Resources into Ontologies
With the goal of speeding up the ontology development process, ontology engineers are starting to reuse as much as possible available ontologies and non-ontological resources such as classification schemes, thesauri, lexicons and folksonomies, that already have some degree of consensus. The reuse of such non-ontological resources necessarily involves their re-engineering into ontologies. Non-ontological resources are highly heterogeneous in their data model and contents: they encode different types of knowledge, and they can be modeled and implemented in different ways. In this paper we present (1) a typology for non-ontological resources, (2) a pattern based approach for re-engineering non-ontological resources into ontologies, and (3) a use case of the proposed approach
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Integration with Ontologies
One of today’s hottest IT topics is integration, as bringing together information from different sources and structures is not completely solved. The approach outlined here wants to illustrate how ontologies [Gr93] could help to support the integration process
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