Tree Segmentation-Based Ontology Mapping

The Information and Communication Technologies (ICT) advancement has made available a huge amount of disparate information. The problem of managing heterogeneity among various information resources is increasing. The Semantic Web also known as the Web of Data is an extension of the hypertext Web. It enables the exchange and integration of data over the Web, in order to achieve the cooperation of humans and machines on a novel, world-wide scale. Ontologies are a pillar of the emerging Semantic Web also plays a vital role in the emerging Semantic Web, and ontology mapping is a crucial part of ontology query and integration.The proliferation in the number of ontologies brings problems in querying multiple ontologies that are possibly heterogeneous and independently developed, and the expansion of ontology size poses challenges in system efficiency and management. As the number of ontologies keeps growing, ontology sharing and reuse become urgent problems. Mapping between different ontologies is the key to solve the problems of ontology communication and interoperation.Presently, many mapping strategies have been developed which can deal with corresponding semantic information in ontologies, and most well-developed ontology mapping systems combine the results of several strategies to get a better one. Ontology mapping is the key to solve the heterogeneous nature of the web. This thesis is mainly focused on these concerns. Initially, the research background of the thesis is briefly introduced, after which the state of the art of the ontology mapping technology is elaborated, as well as the development style of the mapping technology.Furthermore, aiming at the problematic of reasonably low efficiency for the current ontology mapping algorithms in the aspect of time outflow, the anticipated work is an ontology mapping method based on sub-tree mapping is proposed. It first divides the ontology into a set of sub-trees with different granularities according to the structure of the ontology, and then uses sub-tree mapping algorithm to map them. Afterwards, the time complexity of the Tree Segmentation Algorithm and Sub-tree Mapping Algorithm are analyzed respectively. Time complexity on algorithm and the experimental results show that the proposed method has made great improvement on the mapping efficiency compared with the current mapping algorithms while preserving the mapping precision and recall. To improve the performance of ontology mapping system, multi-strategy combination is often needed. Every strategy has its own advantages and disadvantages. Former combinations give different weight to strategies, and then compute weighted average. This work presents Tree Segmentation-Based Ontology Mapping and it demonstrations that proposed algorithm efficiently improves the precision while maintaining recall.Finally, aiming at the problem of discovering only the simplest complex mappings for the current complex mapping algorithms, a complex mapping method based on the containing relation and equivalent relation is proposed. It first discovers complex mappings by using information provided by the existed mappings, instance and property and so on which are based on the containing relation, and then finds mappings from the characteristic of equivalent nodes and equivalent patterns which are based on the equivalent relation. Experimental results indicate that the proposed method is moderately, significant improvement over existing approaches.