Academic Collaboration Recommendation Based on Sparse Distributed Representation

Abstract

The researchers with similar research contents are helpful for understanding the relevant field and the promotion of further exchanges and collaborations. Find proper researchers is a complex task, we proposed an innovative approach of collaboration recommendation based on sparse distributed representation (SDR). According to the sparse distributed representation theory, the text contents of authors' thesis are characterized to vectors, then recommend collaborations based on the similarity of vectors. We also validate our approach using the data set of NIPS, the experimental results show that the method we proposed is effectively used for collaborative recommendation.