SVM-based algorithms for aligning ontologies using literature

Abstract: Ontologies is one of the key techniques used in Semantic Web establishment. Nowadays，many ontologies have been developed and it is critical to understand the relationships between the terms of the ontologies, i.e. we need to align the ontologies. This thesis deals with an approach for finding relationships between ontologies using literature by classifying documents related to terms in the ontologies.   In this project the general method from [1] is used, but in the classifier generation part, a brand new classifier based on SVMs algorithm is implemented by LPU and SVMlight. We evaluate our approach and compare it to previous approaches.