OOPS! (OntOlogy Pitfall Scanner!): a web-based tool for ontology evaluation

In this paper we present a model for building ontology translation systems between ontology languages and/or ontology tools, where translation decisions are defined at four

The KR ontology implemented contains only the ontology components that cannot be represented directly in the standard knowledge model of the target format, so that they are only

In previous work (Fernández-Tobías et al., 2011) we proposed a semantic-based framework that aims to extract and aggregate DBpedia concepts and relations between

In fact, KIM relies on a keyword-based IR engine for this purpose (indexing, retrieval and ranking). Our work complements KIM with a ranking algorithm specifically designed for

However, the same as traditional IR is based on character strings (keywords), current multimedia retrieval approaches mainly rely on low- level content features (pixels,

o Pattern-based extraction [Hearst, 1992; Morin, 1999]: a relation is recognized when a sequence of words in the text matches a pattern. For instance, a pattern can establish that

In [15], a framework to semi-automate the semantic annotation of Web services (i.e. parameter description based on ontology concepts, semantic service classification, etc.)

The resulting OWL DL ontology (in its primary version) consists of 205 concepts linked with 73 relations (OWL properties). A screenshot of this ontology is presented in Fig.1. The