Blei, D., A.Y. Ng, and M. Jordan. 2003. “LatentDirichletAllocation.” Journal of Machine Learning Research 3: 993–1022. Available at: http://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf (accessed May 2016).
Blei, D. and J. Lafferty. 2006. “Dynamic Topic Models.” Proceedings of the 23rd International Conference on Machine Learning, 113–120, Pittsburgh, Pennsylvania, U.S.A., June 25 – 29, 2006. Doi: https://doi.org/10.1145/1143844.1143859 .
Blei, D. and J. Lafferty. 2007. “A Correlated Topic Model of Science.” Annals of
Minhui Xue, Gabriel Magno, Evandro Cunha, Virgilio Almeida and Keith W. Ross
’s search results. http://www.bbc.co.uk/blogs/internet/entries/1d765aa8-600b-4f32-b110-d02fbf7fd379, 25 June, 2015.
 BBC. BBC forgotten list “sets precedent”. http://www.bbc.com/news/technology-33287758, 26 June, 2015.
 Bert-Jaap Koops. Forgetting footprints, shunning shadows: A critical analysis of the “Right to be Forgotten” in big data practice. SCRIPTed, 8(3):229-256, Dec. 2011.
 D. M. Blei, A. Y. Ng, and M. I. Jordan. LatentDirichletAllocation. the Journal of machine Learning research, 3:993-1022, 2003
research works on microblog influence are abundant. However, research on the influence of microblog in specific fields, such as public health emergencies, is relatively insufficient. This study attempts to propose a microblog influence prediction model for public health emergencies, which is composed of user, time, and content features and which uses the random forest method ( Breiman, 2001 ) and the Best Match 25-based latentDirichletallocation model (LDA-BM25) ( Li, 2013 ). As this model is constructed specifically for public health emergencies, it highlights the
4. Blei, D. M., A. Y. Ng, M. I. Jordan. LatentDirichletAllocation. - Journal of Machine Learning Research, Vol. 3, 2003, No 4, pp. 993-1022.
5. Liu, Q., H. Ma, E. Chen, H. Xiong. A Survey of Context-Aware Mobile Recommendations. - International Journal of Information Technology and Decision Making, Vol. 12, 2013, No 1, pp. 139-172.
6. Pan, Y., L. Luo, D. Liu. How to Recommend by Online Lifestyle Tagging. - International Journal of Information Technology and Decision Making, Vol. 13, 2014, No 6, pp. 1183-1209.
Helle Sjøvaag, Truls André Pedersen and Ole Martin Lægreid
analysis of the level of localism and journalistic professionalism in the Norwegian local media system. The analysis is based on structural analysis as well as a mix of descriptive and predictive statistical analyses on a corpus of 847,487 digital news articles collected from 156 online newspapers in 2015–2017, using LatentDirichletAllocation (LDA) topic modelling. The extent to which these assumptions are supported in turn enables a discussion of how local media system features contribute to media systems theory.
In the following, we first discuss the relevant
collection of pseudo-documents. Such hidden topics serve as the auxiliary knowledge to regulate the topic learning process in SSCF. On two real-world datasets in two languages, experimental results show that the proposed SSCF consistently achieves better classification accuracy than state-of-the-art dataless baselines in terms of F 1 . We also observe that SSCF can even achieve superior performance to supervised classifiers supervised latentdirichletallocation (sLDA) and support vector machine (SVM) on some specific tasks. To summarize, the main contributions of this
Xianlei Dong, Jian Xu, Ying Ding, Chenwei Zhang, Kunpeng Zhang and Min Song
included. PubMed data and Google Trends time-series data can be matched. Since Google Trends data can be provided weekly and PubMed data are released monthly, we convert all weekly data to monthly by taking a four-week moving average. For every selected topic discussed above, we obtain Google Trends time-series data from January 2004 to January 2013.
The overall framework of the methodology is shown in Figure 2 , including generating topics from the obesity corpus using the latentDirichletallocation (LDA) algorithm ( Blei, Ng, & Jordan, 2003
Kannan R. Jagadeesh, Ankush Rai, Janusz Szpytko and Yashesh C. Pandya
information processing systems, 18, 147, 2006.
 Blei, D. M., Ng, A. Y., Jordan, M. I., LatentDirichletallocation , Journal of Machine Learning Research, 3, 993-1022, 2003.
 Rai, A., Artificial Intelligence for Emotion Recognition , Journal of Artificial Intelligence Research & Advances, 1(2), 24-30, 2014.
 Rai, A., Sakkaravarthi Ramanathan, Kannan, R. J., Quasi Opportunistic Supercomputing for Geospatial Socially Networked Mobile Devices , Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), IEEE 25th International
Berge, C. Graphs and hypergraphs. North-Holland Pub. Co., 1976.
Blei, D.M. and J.D. Lafferty. A correlated topic model of science. Annals of Applied Statistics , 1 (1):17-35, 2007.
Blei, D.M., A.Y. Ng, and M.I. Jordan. LatentDirichletallocation. The Journal of Machine Learning Research , 3:993-1022, 2003.
Blei, D., T.L. Griffiths, M.I. Jordan, and J.B. Tenenbaum. Hierarchical topic models and the nested Chinese restaurant process. Advances
Ronald Cardenas, Kevin Bello, Alberto Coronado and Elizabeth Villota
’06) , pages 113–120, August 2006.
Blei, D. M., A. Ng, and M. I. Jordan. LatentDirichletAllocation. Journal of Machine Learning Research , 3:993–1022, 2003.
Blei, D. M., T. L. Griffiths, and M. I. Jordan. The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies. Journal of the ACM , 57:7.1–7.30, 2007.
Cardenas Acosta, Ronald, Kevin Bello Medina, Alberto Coronado, and Elizabeth Villota. Engineering job ads corpus, 2016. URL http://hdl.handle.net/11234/1-2673 . LINDAT/CLARIN digital library at the Institute