This paper proposes lexical annotation as an effective method to solve the ambiguity problems that affect ontology matchers. Lexical annotation associates to each ontology element a set of meanings belonging to a semantic resource. Performing lexical annotation on theontologies involved in the matching process allows to detect false positive mappings and to enrich matching results by adding new mappings (i.e. lexical relationships between elements on the basis of the semanticrelationships holding among meanings).The paper will go through the explanation of how to apply lexical annotation on the results obtained by a matcher. In particular, the paper shows an application on the SCARLET matcher.We adopt an experimental approach on two test ca...
Abstract—Matching ontologies which utilize significantly hetero-geneous terminologies is a challengi...
International audienceThis paper presents how the online tool GREW-MATCH can be used to make queries...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
This paper\u2019s aim is to examine what role Lexical Knowledge Extraction plays in data integration...
In this paper, we introduce Wiktionary Matcher, an ontology matching tool that exploits Wiktionary a...
A new paradigm in Semantic Web research focuses on the development of a new generation of knowledge-...
Semantic matching is a computational process that aims to automatically identify the semantic relati...
Abstract. A new paradigm in Semantic Web research focuses on the development of a new generation of ...
We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexi...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
This paper presents the results of the Wiktionary Matcher in the Ontology Alignment Evaluation Initi...
Semantic Web applications require robust and accurate annotation tools that are capable of automatin...
This paper presents the results of the Wiktionary Matcher in the Ontology Alignment Evaluation Initi...
Abstract—Matching ontologies which utilize significantly hetero-geneous terminologies is a challengi...
International audienceThis paper presents how the online tool GREW-MATCH can be used to make queries...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
This paper\u2019s aim is to examine what role Lexical Knowledge Extraction plays in data integration...
In this paper, we introduce Wiktionary Matcher, an ontology matching tool that exploits Wiktionary a...
A new paradigm in Semantic Web research focuses on the development of a new generation of knowledge-...
Semantic matching is a computational process that aims to automatically identify the semantic relati...
Abstract. A new paradigm in Semantic Web research focuses on the development of a new generation of ...
We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexi...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
This paper presents the results of the Wiktionary Matcher in the Ontology Alignment Evaluation Initi...
Semantic Web applications require robust and accurate annotation tools that are capable of automatin...
This paper presents the results of the Wiktionary Matcher in the Ontology Alignment Evaluation Initi...
Abstract—Matching ontologies which utilize significantly hetero-geneous terminologies is a challengi...
International audienceThis paper presents how the online tool GREW-MATCH can be used to make queries...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...