Pattern-based core word recognition to support ontology matching

Abstract

http://www-sop.inria.fr/members/Fuqi.Song/files/Pattern-based%20core%20word%20recognition%20to%20support%20ontology%20matching.%20Fuqi%20Song.pdfInternational audienceOntology matching is a crucial issue in the domain of semantic web and data interoperability. In this paper, a core word based method for measuring similarity from the semantic level of ontology entities is described. In ontology, most labels of entities are compound words rather than single meaningful words. However, the main meaning is represented usually by one word of them, which is called core word. The core word is learned by investigating certain patterns, which are defined based on part of speech (POS) and linguistics knowledge. The other information is noted as complementary information. An algorithm is given to measure the similarity between a pair of compound words and short texts. In order to support diverse situation, especially when core words cannot be recognized, non semantic based ontology matching techniques are applied from lexical and structural level of ontology. The described method is tested on real ontology and benchmarking data sets. It showed good matching ability and obtained promising results

A Utilization Framework of Ubiquitous Resources for Service Robots Using Semantic Matchmaking

“…When no taxonomy information is available, a broad edit distance metric [22] (Jaro-Winkler distance) is applied.…”

“…When no taxonomy information is available, a broadly edit distance metric [22] (Jaro-Winkler distance) is applied. Denote m as the number of matching characters and t as half the transportation number.…”

“…In some approaches, more information about ontology is adopted, for example, the data type and value may be used to calculate the similarity [20]. While string metric is the most-commonly used technique [21], Song [22]proposes a core word-based method for measuring similarity from the semantic level of ontology entities.…”