User Algorithm based on Social Network

Hean LIU, Zhike KUANG

Hunan City University, Yiyang Hunan 413000, CHINA

Abstract: To deal with the issues like existing common data sparseness in weibo social network and the phenomena

of cold start, this paper puts forward a two-stage clustering based on the recommendation algorithm

GCCR. At the same time, because of fuzziness of graph clustering, this thesis retains a certain diversity in the

process of user interest clustering, so as to avoid convergence too fast when cold start. This method is verified

through the real social network data, and the experimental results show that this algorithm can effectively

solve the problems such as data sparseness and cold start phenomenon.

Keywords: Collaborative filtering; Clustering; Data set; Fuzzy degree