Automatic Discovery of Relationship Between Examination Question and Knowledge Points Based on Vector Space Model

doi:10.3969/j.issn.1006-2475.2015.10.002

Abstract

Abstract: With the extensive application of examination system based on knowledge points, how to automatically match examination question with knowledge points has become an important direction of current research. In this paper, word2vec is used to get the K-dimensional space vector for each word in the texts of examination question and the knowledge points at first. And then, we calculate the cosine distance between the vectors to represent the semantic similarity of the examination question and the knowledge points. The experimental results show that this method can quickly find the relationship between examination question and knowledge points and improve the work efficiency of the examination system.

Key words: word2vec, knowledge point, cosine distance, semantic similarity, vector space model

CLC Number:

TP391

DONG Ao-gen, LIU Mao-fu, HUANG Ge-xin, SHU Qi-yun. Automatic Discovery of Relationship Between Examination Question and Knowledge Points Based on Vector Space Model[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2015.10.002.

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