Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a to...Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a topic mining model based on Latent Dirichlet Allocation(LDA) named user-topic model.For each user,the interests are divided into two parts by different ways to generate the microblogs:original interest and retweet interest.We represent a Gibbs sampling implementation for inference the parameters of our model,and discover not only user's original interest,but also retweet interest.Then we combine original interest and retweet interest to compute interest words for users.Experiments on a dataset of Sina microblogs demonstrate that our model is able to discover user interest effectively and outperforms existing topic models in this task.And we find that original interest and retweet interest are similar and the topics of interest contain user labels.The interest words discovered by our model reflect user labels,but range is much broader.展开更多
给出了面向多异构社交网络(Multi⁃heterogeneous social network,MHSN)的全局表示模型,建立了MHSN用户空间及内容空间的关联模型,为基于MHSN的后续研究提供借鉴。以MHSN的地域突发事件检测为例,论述了基于内容空间的MHSN的融合方法,并...给出了面向多异构社交网络(Multi⁃heterogeneous social network,MHSN)的全局表示模型,建立了MHSN用户空间及内容空间的关联模型,为基于MHSN的后续研究提供借鉴。以MHSN的地域突发事件检测为例,论述了基于内容空间的MHSN的融合方法,并以微博和贴吧进行了数据采集和突发事件检测的实验分析;以MHSN的用户兴趣挖掘为例,论述了基于用户空间的MHSN的融合方法,并以微博和贴吧进行了数据采集和用户兴趣挖掘的实验分析。结果表明,本文所提的面向MHSN的突发事件融合检测及用户兴趣融合挖掘方法可以有效地改善突发事件检测和用户兴趣挖掘的效果。展开更多
基金This work was supported by the National High Technology Research and Development Program of China（No. 2010AA012505, 2011AA010702, 2012AA01A401 and 2012AA01A402）, Chinese National Science Foundation （No. 60933005, 91124002,61303265）, National Technology Support Foundation （No. 2012BAH38B04） and National 242 Foundation （No. 2011A010）
文摘Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a topic mining model based on Latent Dirichlet Allocation(LDA) named user-topic model.For each user,the interests are divided into two parts by different ways to generate the microblogs:original interest and retweet interest.We represent a Gibbs sampling implementation for inference the parameters of our model,and discover not only user's original interest,but also retweet interest.Then we combine original interest and retweet interest to compute interest words for users.Experiments on a dataset of Sina microblogs demonstrate that our model is able to discover user interest effectively and outperforms existing topic models in this task.And we find that original interest and retweet interest are similar and the topics of interest contain user labels.The interest words discovered by our model reflect user labels,but range is much broader.
文摘给出了面向多异构社交网络(Multi⁃heterogeneous social network,MHSN)的全局表示模型,建立了MHSN用户空间及内容空间的关联模型,为基于MHSN的后续研究提供借鉴。以MHSN的地域突发事件检测为例,论述了基于内容空间的MHSN的融合方法,并以微博和贴吧进行了数据采集和突发事件检测的实验分析;以MHSN的用户兴趣挖掘为例,论述了基于用户空间的MHSN的融合方法,并以微博和贴吧进行了数据采集和用户兴趣挖掘的实验分析。结果表明,本文所提的面向MHSN的突发事件融合检测及用户兴趣融合挖掘方法可以有效地改善突发事件检测和用户兴趣挖掘的效果。
