Abstract: A term relation extraction approach was proposed. It was cast as a classification task. The hybrid classification algorithm combining the advantages of both naive bayes and perceptron was also presented. In this algorithm, a subset of the features was estimated from training data, and another subset of the features was trained by discriminative function. The experimental results showed that the proposed hybrid algorithm almost always outperforms the naive bayes algorithms and perceptron algorithms when the training set is small.

Key words: Machine learning,Term relation extraction,Classification algorithm