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Correction: A correlated topic model of Science
, 2007 Correction to Annals of Applied Statistics 1 (2007) 17--35 [doi:10.1214/07-AOAS114]Comment: Published in at http://dx.doi.org/10.1214/07-AOAS136 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical ...
Blei, David M., Lafferty, John D.
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Modeling Topic and Role Information in Meetings using the Hierarchical Dirichlet Process [PDF]
, 2008 . In this paper, we address the modeling of topic and role information in multiparty meetings, via a nonparametric Bayesian model called the hierarchical Dirichlet process.
Huang, Songfang, Renals, Steve
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Inferring Inter-City Trip Purpose From the Perspective of the Group
IEEE Access, 2021 Although trip purpose inference based on passively collected data has long been investigated, less attention has been paid to inter-city trips. The reason is, except using ticket sales data, only limited trips can be extracted due to the lower frequency ...
Jianpei Qian +3 more
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Stochastic Divergence Minimization for Biterm Topic Model
, 2017 As the emergence and the thriving development of social networks, a huge number of short texts are accumulated and need to be processed. Inferring latent topics of collected short texts is useful for understanding its hidden structure and predicting new ...
Cui, Zhenghang +2 more
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A correlated topic model of Science
, 2007 Topic models, such as latent Dirichlet allocation (LDA), can be useful tools for the statistical analysis of document collections and other discrete data. The LDA model assumes that the words of each document arise from a mixture of topics, each of which
Blei, David M., Lafferty, John D.
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Discriminative Relational Topic Models [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 Many scientific and engineering fields involve analyzing network data. For document networks, relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents, and they have shown promise on predicting network structures and discovering latent topic representations.
Chen, Ning +3 more
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Applied Sciences, 2022 The personalized recommendation system is a useful tool adopted by e-retailers to help consumers to find items in line with their preferences. Existing methods focus on learning user preferences from a user-item matrix or online reviews after purchasing,
Xin Huang, Xiaojuan Liu
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New topic detection in microblogs and topic model evaluation using topical alignment [PDF]
, 2014 textThis thesis deals with topic model evaluation and new topic detection in microblogs. Microblogs are short and thus may not carry any contextual clues.
Rajani, Nazneen Fatema
core
When Topic Models Disagree [PDF]
Proceedings of the 24th International Conference on World Wide Web, 2015 We explore how the unsupervised extraction of topic-related keywords benefits from combining multiple topic models. We show that averaging multiple topic models, inferred from different corpora, leads to more accurate keyphrases than when using a single topic model and other state-of-the-art techniques. The experiments confirm the intuitive idea that a
Sterckx, Lucas +3 more
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mSystems, 2020 Gut dysbiosis has been repeatedly reported in Parkinson’s disease (PD) but only once in idiopathic rapid-eye-movement sleep behavior disorder (iRBD) from Germany.
Hiroshi Nishiwaki +13 more
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