istributed Latent Dirichlet Allocation for Objects-Distributed Cluster Ensemble

摘要：

The paper introduces the model of distributed latent Dirichlet location (D-LDA) for objects-distributed cluster ensemble which can handle the problems of privacy preser-vation,distributed computing and knowledge reuse. First, the latent variables in D-LDA and some terminologies are dened for cluster ensemble. Second, Markov chain Monte Carlo(MCMC)approximation inference for D-LDA is stated in detail. Third, some datasets from UCI are chosen for experiment, Compared with cluster-based similarity par-titioning algorithm (CSPA),hyper-graph partitioning algo-rithm(HGPA) and meta-clustering algorithm(MCLA), the results show D-LDA does work better, furthermore the out-puts of D-LDA, as a soft cluster model, can not only cluster the data points but also show the structure of data points.

作者: Hongjun WANG Zhishu LI Yang CHENG

作者单位: School of Computer Science,chuan University,610054 Chengdu,China School of Computer Science,Sichuan University,610054 Chengdu,China

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）