Using the Semantic Web as Background Knowledge for Ontology Mapping
This event took place on Wednesday 15 November 2006 at 12:15
Dr. Marta Sabou KMi, The Open University
While current approaches to ontology mapping produce good results by mainly relying on label and structure based similarity measures, there are several cases in which they fail to discover important mappings. In this paper we describe a novel approach to ontology mapping, which is able to avoid this limitation by using background knowledge. Existing approaches relying on background knowledge typically have one or both of two key limitations: 1) they rely on a manually selected reference ontology; 2) they suffer from the noise introduced by the use of semi-structured sources, such as text corpora. Our technique circumvents these limitations by exploiting the increasing amount of semantic
resources available online. As a result, there is no need either
for a manually selected reference ontology (the relevant ontologies are dynamically selected from an online ontology repository), or for transforming background knowledge in an ontological form. The promising results from experiments on two real life thesauri indicate both that our approach has a high precision and also that it can find mappings, which are typically missed by existing approaches.
Download presentation slides
This event took place on Wednesday 15 November 2006 at 12:15
While current approaches to ontology mapping produce good results by mainly relying on label and structure based similarity measures, there are several cases in which they fail to discover important mappings. In this paper we describe a novel approach to ontology mapping, which is able to avoid this limitation by using background knowledge. Existing approaches relying on background knowledge typically have one or both of two key limitations: 1) they rely on a manually selected reference ontology; 2) they suffer from the noise introduced by the use of semi-structured sources, such as text corpora. Our technique circumvents these limitations by exploiting the increasing amount of semantic
resources available online. As a result, there is no need either
for a manually selected reference ontology (the relevant ontologies are dynamically selected from an online ontology repository), or for transforming background knowledge in an ontological form. The promising results from experiments on two real life thesauri indicate both that our approach has a high precision and also that it can find mappings, which are typically missed by existing approaches.
Download presentation slides
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
New Media Systems is...
Our New Media Systems research theme aims to show how new media devices, standards, architectures and concepts can change the nature of learning.
Our work involves the development of short life-cycle working prototypes of innovative technologies or concepts that we believe will influence the future of open learning within a 3-5 year timescale. Each new media concept is built into a working prototype of how the innovation may change a target community. The working prototypes are all available (in some form) from this website.
Our prototypes themselves are not designed solely for traditional Open Learning, but include a remit to show how that innovation can and will change learning at all levels and in all forms; in education, at work and play.
List all New Media Systems Projects
Check out these Hot New Media Systems Technologies:
List all New Media Systems Technologies
