An Approach to Mapping Relational Databases to Ontologies
Date Issued
2007
Date
2007
Author(s)
Cheng, Yi-Shan
DOI
en-US
Abstract
Web Service technology allows uniform access via Web standards as software components residing on various platforms. As the scale of Web Services becomes larger, finding the suitable Web Services is a non-trivial work. Currently, most users find Web Services by keyword search and manually read the description contents of the services. This work is time consuming and lack of efficiency. The Semantic Web is a machine understandable Web annotated by ontologies. By applying Semantic Web technology to Web Services, we can make Web Services to be machine-understandable. Most people use ontology definitions as the basis of semantic annotation on Semantic Web. Consequently, automatic construction of ontologies from existing information is relevant. Relational databases are the most common type of data storing system. For service providers who want to participate in Semantic Web services, to find out the mappings between their legacy relational database to ontologies is seen as an critical issue.
In this thesis, we develop an approach to mapping a relational database schema to a specified domain ontology herewith the legacy relational database could be applicable
to Semantic Web services. The mapping algorithm consists of two phases to find the optimal mappings. The first phase is the Element-Level Matching which aims to measure
the similarity of a single table and a single class. This phase of matching matches all possible combinations of a table and a class, measures their similarity by their names and the names of their columns and properties, using natural language processing techniques. The second matching phase is the Schema-Level Matching, which considers the overall structures of both schemas. Intuitively, for a table and a class, the more their associated tables and associated classes are similar, the higher possibility that they would be actually mapped. The matchers of the Schema-Level Matching phase measure the structural similarity by their sub-tables/classes, super-tables/classes, the tables that referring to/referred to by the table, and the classes associated by object properties. The overall match score of a table and a class is composed of the two match scores which are calculated
by the two matching phases. Because of the different development goal of these two schemas and the various designing styles, it is impractical to expect the high accuracy of full-automatic mapping. Our system therefore would choose several top mappings for each table as candidates to be chosen by the user.
Subjects
知識本體
知識本體語言
語意網
對映
網路服務
關聯式資料庫
Ontology
OWL
SemanticWeb
Mapping
Web Services
Relational Databases
Type
other
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