Course Similarity Calculation Using Efficient Manifold Ranking
Bingjie Zhao, Xueqing Li · Lecture notes in computer science · 2015
Course Similarity Calculation aims at quantitatively computing the cross degree of the knowledge points two courses contain. However, the polysemy and synonym of various knowledge points lead to the main challenge for calculation effectiveness. Existing course similarity calculation methods are mainly based on the traditional text mining approaches such as Latent Semantic Indexing (LSI) and Term Frequency-Inverse Document Frequency (TFIDF). However, these methods calculate the similarity between two courses simply by their absolute pairwise distance, which significantly limits the effectiveness of capturing the semantic relevance among all the courses. In this paper, we propose a novel course similarity calculation method using Efficient Manifold Ranking (EMR), which improves the traditional methods by measuring course similarities considering the underlying intrinsic manifold structure on the whole dataset. Experimental results on a real world course database demonstrate the outstanding performance of our proposed method. Furthermore, we extend the proposed method to major similarity calculation.