A feature optimization algorithm of concept similarity based on Chinese wikipedia

Concept similarity measure based on feature vector has wide application in various fields, but the problems of polysemy and synonym existing in feature vector affect the similarity measure. We present a feature optimization algorithm based on Chinese Wikipedia which can reduces this effect. First we build a POS feature dictionary (POS-Dic) and a POS Tongyici Cilin(POS-Cilin), and then a new feature vector is used for concept similarity measure. Experiments show that the algorithm effectively reduces the influence of polysemy and synonym on the concept similarity measure.