Solving Semantic Ambiguity to Improve Semantic Web based Ontology Matching

A new paradigm in Semantic Web research focuses on the development of a new generation of knowledge-based problem solvers, which can exploit the massive amounts of formally specified information available on the Web, to produce novel intelligent functionalities. An important example of this paradigm can be found in the area of Ontology Matching, where new algorithms, which derive mappings from an exploration of multiple and heterogeneous online ontologies, have been proposed. While these algorithms exhibit very good performance, they rely on merely syntactical techniques to anchor the terms to be matched to those found on the Semantic Web. As a result, their precision can be affected by ambiguous words. In this paper, we aim to solve these problems by introducing techniques from Word Sense Disambiguation, which validate the mappings by exploring the semantics of the ontological terms involved in the matching process. Specifically we discuss how two techniques, which exploit the onto...

• Type: Conference
• Year: 2007
• Where: SEMWEB
• Authors: Jorge Gracia, Vanessa Lopez, Mathieu d'Aquin, Marta Sabou, Enrico Motta, Eduardo Mena
• Keywords: Knowledge-based Problem Solvers, Semantic Web, Semantic Web Research, SEMWEB 2007