2004
DOI: 10.1007/978-3-540-30145-5_13
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Semantic Information Interoperability in Open Networked Systems

Abstract: Abstract. In open networked systems, each node shares part of its informational resources on the network and is responsible of providing an ontological description for them. To enable semantic information interoperability in networked contexts with a multitude of autonomous ontologies, appropriate matching techniques are required to determine semantic mappings between concepts of different ontologies. In this paper, we describe H-Match, an algorithm for dynamically performing ontology matching in open networke… Show more

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Cited by 21 publications
(15 citation statements)
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“…Castano et al [9] describe the H-Match algorithm to dynamically match ontologies. H-Match provides, for each concept from an ontology, a ranked list of similar concepts in the other ontology.…”
Section: Related Workmentioning
confidence: 99%
“…Castano et al [9] describe the H-Match algorithm to dynamically match ontologies. H-Match provides, for each concept from an ontology, a ranked list of similar concepts in the other ontology.…”
Section: Related Workmentioning
confidence: 99%
“…Most schema matching algorithms (Li et al, 2000), (Doan et al, 2003), (Mitra et al, 2000), (Milo and Zohar, 1998), (Palopoli et al, 2000), (Castano et al, 2004), (Do and Rahm, 2001), (Melnik et al, 2002), (Noy and Musen, 2001), (Giunchiglia et al, 2004) produce similarity scores between source and target schemas nodes such as the ones we produce in section 5.3; however, such a mapping result partially solves the problem. First, produced similarities between individual nodes are not enough to produce access paths for retrieving data from the available sources.…”
Section: Discovery Of Nodes and Edges Matchesmentioning
confidence: 99%
“…To support the matchmaking between the request and the advertisement, the knowledge contained in the domain ontology DomON T is extended by means of a thesaurus T H, where terms used as names of ontological concepts are related to other terms by means of terminological relationships (e.g., synonymy, hypernymy, hyponymy, etc.). Following a procedure similar to that proposed by [9], the thesaurus T H is automatically derived by considering the set T of terms denoting atomic concepts in DomON T and the lexical system WordNet [12]. To be compliant with real ontologies, where names can be composed by one or more terms, we select terms and terminological relationships to be stored in T H as follows.…”
Section: Semantic Infrastructure For Service Discoverymentioning
confidence: 99%