Generating Cohesive Semantic Topics from Latent Factors
暂无分享,去创建一个
[1] Ming-Syan Chen,et al. Mining Web informative structures and contents based on entropy analysis , 2004, IEEE Transactions on Knowledge and Data Engineering.
[2] Qiaozhu Mei,et al. One theme in all views: modeling consensus topics in multiple contexts , 2013, KDD.
[3] Jaegul Choo,et al. UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization , 2013, IEEE Transactions on Visualization and Computer Graphics.
[4] ChenMing-Syan,et al. Mining Web Informative Structures and Contents Based on Entropy Analysis , 2004 .
[5] Xueqi Cheng,et al. Group sparse topical coding: from code to topic , 2013, WSDM.
[6] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[7] Rafael Berlanga Llavori,et al. Topic discovery based on text mining techniques , 2007, Inf. Process. Manag..
[8] Stéphane Ducasse,et al. Semantic clustering: Identifying topics in source code , 2007, Inf. Softw. Technol..
[9] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[10] Quan Wang,et al. Group matrix factorization for scalable topic modeling , 2012, SIGIR '12.
[11] Chih-Jen Lin,et al. On the Convergence of Multiplicative Update Algorithms for Nonnegative Matrix Factorization , 2007, IEEE Transactions on Neural Networks.
[12] Xiaohui Yan,et al. Learning Topics in Short Texts by Non-negative Matrix Factorization on Term Correlation Matrix , 2013, SDM.
[13] Michael W. Berry,et al. Algorithms and applications for approximate nonnegative matrix factorization , 2007, Comput. Stat. Data Anal..
[14] Ian H. Witten,et al. Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.
[15] Marcel Abendroth,et al. Data Mining Practical Machine Learning Tools And Techniques With Java Implementations , 2016 .