论文标题
具有同质性系统的新的优惠模型
A new preferential model with homophily for recommender systems
论文作者
论文摘要
“ Rich-Get-Richer”和“同性恋”是不断发展的社交网络中的两个重要现象。 “ Rich-Get-Richer”是指具有较高追随者的人更有可能吸引新粉丝，而“同质性”意味着人们更喜欢与同一社会群体的其他人建立联系或具有其他共同点的人。为了在不断发展的社交网络的背景下同时正式化现象，我们考虑了K组优先附件（KPA）网络模型，这对社交网络推荐系统有帮助。本文的主要贡献是提出一种新的不断发展的社交网络模型，其机制丰富和同质的机制。我们表明，KPA模型为每个组具有幂律度分布，并证明了KPA模型中参数的最大似然估计（MLE）的中心极限定理（CLT）。我们通过模拟数据来说明我们的结果，并使用真实的数据示例探索该模型的使用情况。
"Rich-get-richer" and "homophily" are two important phenomena in evolving social networks. "Rich-get-richer" means people with higher followings are more likely to attract new fans, and "homophily" means people prefer to bond with others of the same social group or who have some other attribute in common. To formalize the phenomena simultaneously in the context of an evolving social network, we consider a K-groups preferential attachment (KPA) network model, which is helpful for the social networks recommender system. The main contribution of this paper is to propose a new evolving social network model with the mechanisms of rich-get-richer and homophily. We show that the KPA model exhibits a power-law degree distribution for each group and prove the central limit theorem (CLT) for the maximum likelihood estimation (MLE) of the parameters in the KPA model. We illustrate our results through simulated data and explore the usage of this model with real data examples.
