CAJ | 학술논문

将TLP和本体回归算法相融合，提出基于TLP经验模型的本体相似度计算和本体映射算法。新算法继承了TCP的特点，使其具有无偏参数估计的特征。将新算法应用于GO本体和物理教育本体，通过实验结果表明新算法对特定的应用领域具有较高的效率。
장TLP화본체회귀산법상융합，제출기우TLP경험모형적본체상사도계산화본체영사산법。신산법계승료TCP적특점，사기구유무편삼수고계적특정。장신산법응용우GO본체화물리교육본체，통과실험결과표명신산법대특정적응용영역구유교고적효솔。
〔Abstract〕By combing truncated Lasso penalty (TLP) with ontology regression algorithm, this paper proposes the new ontology similarity computation and ontology mapping algorithm based on TLP empirical model. The new algorithm inherits the characteristics of TCP and has the quality of unbiased parameter estimation. The experiment shows that the new algorithm achieves higher efficiency in specific applications when it is applied to the GO and the physical education ontology.