Ontology learning algorithm based on regularization model under noise condition
Zhu Lin-l · Journal of Northwest Normal University · 2014
The regularization ontology model is improved by using the reproducing kernel Hilbert space and linear space of Rm,and a new regularization model in semi-supervised learning setting is obtained.This new model focuses on the designing of hypothesis space.Two experiments show that the new algorithm for specific applications has higher efficiency.