DISTRIBUTED LATENT DIRICHLET ALLOCATION FOR DISTRIBUTED CLUSTER ENSEMBLE

作者：Wang Hongjun^*; Qi Jianhuai; Zheng Weifan; Wang Mingwen

来源：International Journal of Innovative Computing Information and Control, 2010, 6(3B): 1461-1470.

• Distributed cluster ensemble
• Distributed latent
• Dirichlet allocation
• Privacy preservation

Cluster ensemble is becoming an important research pot and many researchers study in this field But there is no author to state the problem of distributed cluster ensemble In this paper the authors initiatively state the problem and introduce the model of distributed latent Dirichlet allocation (D-LDA) for distributed cluster ensemble which is the most important contribution of this paper First, the latent variables in D-LDA and some terminologies are defined for distributed 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 experiments Compared with cluster-based similarity partitioning algorithm (CSPA), hyper-graph partitioning algorithm and meta-cluster algorithm (MCLA), the results show D-LDA does work better, further-more Me outputs of D-LDA, as a soft cluster model, Can not only cluster the, data ponds but also show the structure of data points

• 出版日期2010-3
• 单位西南交通大学