Research on human behavior has attracted increasing attention recently because of its scientific significance and potential applications.Some empirical results have indicated that the timing of many human activities f...Research on human behavior has attracted increasing attention recently because of its scientific significance and potential applications.Some empirical results have indicated that the timing of many human activities follows non-Poisson statistics.We analyze a real-life huge dataset of short message communication with 6326713 users and 37577781 records during the 2006 Chinese New Year.The results show that the number of short message sendings,the interevent time between two consecutive short message sendings and the response time all follow heavy-tailed distribution.We further observe a strongly positive correlation between the activity and the power-law exponent of the interevent time distribution.In addition,the short message communication system displays a bursty property yet no memory effects,which is in particular different from some well-studied human-activited systems such as email-sending,library-loaning and file printing.展开更多
We employ a bipartite network to describe an online commercial system.Instead of investigating accuracy and diversity in each recommendation,we focus on studying the influence of recommendation on the evolution of the...We employ a bipartite network to describe an online commercial system.Instead of investigating accuracy and diversity in each recommendation,we focus on studying the influence of recommendation on the evolution of the online bipartite network.The analysis is based on two benchmark datasets and several well-known recommendation algorithms.The structure properties investigated include item degree heterogeneity,clustering coefficient and degree correlation.This work highlights the importance of studying the effects and performance of recommendation in long-term evolution.展开更多
基金by the National Natural Science Foundation of China under Grant Nos 90924011,60973069,10975126,70971089 and 70871082the China Postdoctoral Science Foundation under Grant No 201003694the Sichuan Provincial Science and Technology Department under Grant No 2010HH0002.
文摘Research on human behavior has attracted increasing attention recently because of its scientific significance and potential applications.Some empirical results have indicated that the timing of many human activities follows non-Poisson statistics.We analyze a real-life huge dataset of short message communication with 6326713 users and 37577781 records during the 2006 Chinese New Year.The results show that the number of short message sendings,the interevent time between two consecutive short message sendings and the response time all follow heavy-tailed distribution.We further observe a strongly positive correlation between the activity and the power-law exponent of the interevent time distribution.In addition,the short message communication system displays a bursty property yet no memory effects,which is in particular different from some well-studied human-activited systems such as email-sending,library-loaning and file printing.
基金Supported by the National Natural Science Foundation of China under Grant No 61370150the Sichuan Provincial Science and Technology Department(2012FZ0120)the Fundamental Research Fund for the Central Universities under Grant No ZYGX2012J075.
文摘We employ a bipartite network to describe an online commercial system.Instead of investigating accuracy and diversity in each recommendation,we focus on studying the influence of recommendation on the evolution of the online bipartite network.The analysis is based on two benchmark datasets and several well-known recommendation algorithms.The structure properties investigated include item degree heterogeneity,clustering coefficient and degree correlation.This work highlights the importance of studying the effects and performance of recommendation in long-term evolution.
