The Design And Implementation Of Optimization Approaches For Large Scale Ontologies Alignment In SAMBO

The current World Wide Web provides a convenient way for people to acquire information,but it is not capable of manipulating semantics.In other words,people can access data from web pages efficiently but computer programs cannot satisfy effective data reuse and sharing.Tim Berners-Lee as the inventor of World Wide Web together with James Hendler and Ora Lassila,proposed the idea of Semantic Web that is expected as an evolution to existing Web.The knowledge representation for Semantic Web witnessed the development from extensible makeup language(XML)and resource description framework(RDF)to ontologies.A large quantity of researches utilize ontologies to express concepts,relations and relevant semantics in specific domains.However,different researchers may have diverse comprehension about knowledge that brings inconsistent information in same or similar ontologies.For instance,some people will define cell activation as “T-cell activation” or “B-cell activation” while other people may define it as “T Cell Activation” or “B Cell Activation”.This kind of data inconsistency among concepts is not useful for data integration.Thus,people proposed ontology alignment to solve this problem.SAMBO that is an ontology alignment system was designed and implemented by ADIT of Link?ping University in 2005.Shortly after implementation,SAMBO could accomplish most tasks of ontology alignment.But it could not satisfy the alignment of large scale ontologies as the scale grow rapidly.The primary job of this thesis is to optimize existing SAMBO system to fulfill alignment of large scale ontologies.The principal parts of this thesis are as follows.First,we analyze the current top ontology alignment system,AML and LogMap which are capable of aligning large scale ontologies to obtain the features in the design of high-quality systems for large scale ontologies alignment.Then,we give an analysis about existing SAMBO that it should be improved in which aspects.Further figure out to upgrade SAMBO in data structure,database design,parallel matching and so on.Thus propose the design of optimization approaches and give the implementation.Finally,we evaluate the new system with large scale ontologies and acquire desired results.