关键词: 时空集聚性, 地点权重, 分组权重, 多重假设验证

Abstract: Mining university students’ social ties based on their spatio-temporal trajectory is one of the hotspots of educational big data research, some mining methods have also been proposed. In view of the impact of spatio-temporal distribution aggregation, the contribution of spatio-temporal factors to the formation of social ties is comprehended, the location weight and group weight based on Shannon entropy are constructed. The method for inferring Weighted Social Ties based on Multiple Hypothesis Test（WST-MHT） is proposed and used to explore the social ties and intimacy of university students. A lot of experiments have been done with real data sets. The result is compared with the current popular methods of inferring social ties. It is observed that the accuracy by using the WST-MHT is 98.9% at the optimal threshold, and the recall is increased by around 20%.

Key words: spatio-temporal aggregation, location weight, group weight, multiple hypothesis test