P. Yazdizadeh and F. Ameri, A Text Mining Technique for Manufacturing Supplier Classification, Volume 1B: 35th Computers and Information in Engineering Conference, 2015.
DOI : 10.1115/DETC2015-46694

Y. Liu, J. Kung, J. , L. , Y. B. et al., Using Text Mining to Handle Unstructured Data in Semiconductor Manufacturing, Joint e-Manufacturing and Design Collaboration Symposium (eMDC, International Symposium on Semiconductor Manufacturing (ISSM), pp.1-3, 2015.

B. Dong and H. Liu, Enterprise Website Topic Modeling and Web Resource Searc, Sixth International Conference on Intelligent Systems Design and Applications, 2006.
DOI : 10.1109/isda.2006.25

D. Blei, Probabilistic Topic Models, Communications of the ACM, vol.55, issue.4, 2012.

C. Manning, P. Raghavan, and H. Schu?-tze, Introduction to Information Retrieval, 2008.
DOI : 10.1017/CBO9780511809071

T. Hofmann, Probabilistic Latent Semantic Indexing, Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence, 1999.

M. Steyvers and T. L. Griffiths, Probabilistic Topic Models, Latent Semantic Analysis: A Road to Meaning, 2005.
DOI : 10.4324/9780203936399.ch21

M. Masseroli, D. Chicco, and P. Pinoli, Probabilistic Latent Semantic Analysis for prediction of Gene Ontology annotations, The 2012 International Joint Conference on Neural Networks (IJCNN), 2012.
DOI : 10.1109/IJCNN.2012.6252767

R. Alghamdi, A. , and K. , A Survey of Topic Modeling in Text Mining, International Journal of Advanced Computer Science and Applications, vol.6, issue.1, 2015.
DOI : 10.14569/IJACSA.2015.060121

D. M. Blei, A. Y. Ng, and M. I. Jordan, Latent Dirichlet Allocation, Journal of Machine Learning Research, vol.3, pp.993-1022, 2003.

L. Alsumait, D. Barbará, and C. Domeniconi, On-line LDA: Adaptive Topic Models for Mining Text Streams with Applications to Topic Detection and Tracking, 2008 Eighth IEEE International Conference on Data Mining, 2008.
DOI : 10.1109/ICDM.2008.140

T. Shulong, L. Yang, S. Huan, G. Ziyu, Y. Xifeng et al., Interpreting the Public Sentiment Variations on Twitter, IEEE Transactions on Knowledge and Data Engineering, vol.26, issue.5, pp.1158-1170, 2014.
DOI : 10.1109/TKDE.2013.116

Z. Zhongwu, L. Bing, X. Hua, and J. Peifa, Constrained LDA for Grouping Product Features in Opinion Mining, Proceedings of PAKDD, pp.448-459, 2001.

Y. Hu, J. Boyd-graber, B. Satinoff, and A. Smith, Interactive topic modeling, Machine Learning, vol.18, issue.3, pp.423-469, 2013.
DOI : 10.1089/cmb.2011.0040
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.207.5738

T. I. Yang, A. J. Torget, and R. Mihalcea, Topic Modeling on Historical Newspapers, Proceedings of the 5th ACL-HLT Workshop on Language Technology for Cultural Heritage , Social Sciences, and Humanities, pp.96-104, 2011.

T. M. Kodinariya and P. R. Makwana, Review on Determining Number of Cluster in K-Means Clustering, International Journal of Advance Research in Computer Science and Management Studies, vol.1, issue.6, pp.90-95, 2013.