A Study on Automatic Ontology Mapping of Categorical Information

Semantic heterogeneity of information is a major barrier of information and system interoperability. Defining ontology of data and mapping ontologies among heterogeneous information repositories is one approach to achieve interoperability. This paper focuses on the ontology mapping of categorical information, which usually have a tree structure with categories and subcategories. Subcategories can be considered as the definition of their upper level categories. Methods of automatic mapping of categorical information using Naïve Bayes classifier are discussed, and improved algorithms for categorical ontologies mapping are proposed and compared to a standard word-by-word matching algorithm. 1 Background Geographic information is being collected and provided by various information producers. Sharing and retrieving geographic information over the World Wide Web and thereby achieving GIS interoperability is highly desired. However, semantic heterogeneity, which occurs when information from...

• Type: Conference
• Year: 2003
• Where: DGO
• Authors: Naijun Zhou
• Keywords: DGO 2003, DGO 2007, Heterogeneous Information Repositories, Information, Ontology Mapping