Converting object-based thesauri into XML Topic Maps

Abstract

Constructing ontology is considerably time consuming process in general. Since there are a vast amount of thesauri currently available, it may be a feasible solution to exploit thesauri, when constructing ontology in a short period of time. This paper designs and implements a XTM (XML Topic Maps) code converter generating XTM coded ontology from an object based thesaurus. It is an extended thesaurus, which enriches the conventional thesauri with user defined associations, a notion of instances and occurrences associated with them. The reason we adopt XTM is that it is a verified and practical methodology to semantically reorganize the conceptual structure of extant web applications with minimal effort. Moreover, since XTM is conceptually similar to our object based thesauri, recommendation and inference mechanism already developed in our system could be easily applied to the generated XTM ontology. To show that the XTM ontology is correct, we also verify it with onto pia Omnigator and Vizigator, the components of Ontopia Knowledge Suite (OKS) tool.

Rule‐based approach for topic maps learning from relational databases

“…Vizigator allows graphical visualization and navigation of TMs, accepting only TMs syntactically well designed. It has been used for the same purpose in other works (Bold, ; Strau & Lemke, ; Johnsen et al , ). Vizigator accomplishes the complete formal data model for TMs representation (XTM specification) and is based on the ISO/International Electrotechnical Commission 13250 standard.…”