刘铭,王晓龙,刘远超.基于语义的高维数据聚类技术[J].电子学报,2009,37(5):925-929. Liu Ming,Wang Xiao-long,Liu Yuan-chao.Clustering technology for high dimensional data based on semantics[J].Acta Electronica Sinica,2009,37(5):925-929.(in Chinese)
[2]
Wang X,et al.Topical N-grams:Phrase and topic discovery,with an application to information retrieval .Proc of the 7th IEEE International Conference on Data Mining .Omaha,Nebraska,USA,2007.697-702.
[3]
Frey B J,Dueck D.Clustering by passing messages between data points[J].Science,2007,315(5814):972-976.
[4]
Blei D M,et al.Latent dirichlet allocation[J].Journal of Machine Learning Research,2003,3(1):993-1022.
[5]
Newman D,Noh Y,Tally E.Evaluating topic models for digital libraries .Proc of JCDL .Gold Coast,Queensland,Australia,2010.215-224.
[6]
Shehata S,et al.An efficient concept-based mining model for enhancing text clustering[J].IEEE Transactions on Knowledge and Data Engineering,2010,22(10):1360-1371.
[7]
Timothy N R,et al.Statistical topic models for multi-label document classification[J].Machine Learning,2012,88(1-2):157-208.
[8]
Andrzejewski D,Buttler D. Latent topic feedback for information retrieval .Proceedings of 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD) .New York:ACM press,2011.600-608.
[9]
Heinrich G.Parameter estimation for text analysis .http://www.arbylon.net/publications/text-est.pdf,2005.
[10]
Ramage D,Heymann P.Clustering the tagged web .Proc of the Second ACM International Conference on Web Search and Data Mining .Barcelona,Spain,2009.54-63.
[11]
曹娟,张勇东,李锦涛,唐胜.一种基于密度的自适应最优LDA模型选择方法[J].计算机学报,2008,31(10):1780-1786. Cao Juan,Zhang Yong-dong,Li Jin-tao,Tang Sheng.A method of adaptively selecting best LDA model based on density[J].Chinese Journal of Computer,2008,31(10):1780-1787.(in Chinese)
