An approach on the automatic generation of concept weights for test items

This paper proposes a structure that automatically analyzes the parameters of Chinese test items. This structure utilizes latent semantic analysis (LSA) to analyze the relationships of keywords among all test items in an item bank. It also uses the similarity measure to calculate the similarity degree of keywords. We also propose an algorithm, which is similar to the graph-theoretic algorithm, for keyword clustering. The concept weights of each test item can be generated automatically with the proposed automatic generate concept weights.