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Asignación Latente de Dirichlet
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1041por Gonzalez, Gabriela, Vaculik, Kristina, Khalil, Carine, Zektser, Yuliya, Arnold, Corey, Almario, Christopher V, Spiegel, Brennan, Anger, Jennifer“…Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. …”
Publicado 2022
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1042por Liu, Cong-Cong, Dong, Shan-Shan, Chen, Jia-Bin, Wang, Chen, Ning, Pan, Guo, Yan, Yang, Tie-Lin“…MetaDecoder was built as a two-layer model with the first layer being a GPU-based modified Dirichlet process Gaussian mixture model (DPGMM), which controls the weight of each DPGMM cluster to avoid over-segmentation by dynamically dissolving contigs in small clusters and reassigning them to the remaining clusters. …”
Publicado 2022
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1043por Niu, Qian, Liu, Junyu, Kato, Masaya, Shinohara, Yuki, Matsumura, Natsuki, Aoyama, Tomoki, Nagai-Tanima, Momoko“…Correlations between sentiments and the daily infection, death, and vaccination cases were calculated. The latent dirichlet allocation model was applied to identify topics of negative tweets from the beginning of vaccination. …”
Publicado 2022
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1044por Bastiaansen, Jort. A. J., Veldhuizen, Elien E., De Schepper, Kees, Scheepers, Floortje E.“…The interviews were analyzed using the traditional qualitative, hermeneutic phenomenology method as well as latent Dirichlet allocation (LDA), an unsupervised machine learning method clustering words from documents into topics. …”
Publicado 2022
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1045por Westmaas, J Lee, Masters, Matthew, Bandi, Priti, Majmundar, Anuja, Asare, Samuel, Diver, W Ryan“…METHODS: Topic model analysis with latent Dirichlet allocation (LDA) identified themes in US tweets with the term “quit smoking.” …”
Publicado 2022
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1046por Lotto, Matheus, Sá Menezes, Tamires, Zakir Hussain, Irfhana, Tsao, Shu-Feng, Ahmad Butt, Zahid, P Morita, Plinio, Cruvinel, Thiago“…Subsequently, two independent investigators analyzed posts qualitatively to define their authors’ interests, profile characteristics, content type, and sentiment. Latent Dirichlet allocation analysis topic modeling was then applied to find salient terms and topics related to false or misleading content, and their similarity was calculated through an intertopic distance map. …”
Publicado 2022
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1047“…METHODS: We obtained a data set of 9266 Reddit posts from the subreddit \rCOVID19_support, from February 14, 2020, to July 19, 2021. We used the latent Dirichlet allocation (LDA) topic model to identify the topics that were mentioned on the subreddit and analyzed the trends in the prevalence of the topics. …”
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1048“…In Python, topics were modeled by latent Dirichlet allocation. Rule-based sentiment analysis scored interactions by emotional valence. …”
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1049“…Latent Dirichlet Allocation (LDA) is an approach to unsupervised learning that aims to investigate the semantics among words in a document as well as the influence of a subject on a word. …”
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1050“…METHODS: We utilized a topic modeling natural language processing method (more specifically latent Dirichlet allocation). Topic modeling is a popular unsupervised learning technique that can be used to automatically infer topics (ie, semantically related categories) from a large corpus of text. …”
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1051“…Topic modeling using the LDA (Latent Dirichlet Allocation) method and emotion analysis were conducted to analyze the posts from Weibo, China’s primary social media platform. …”
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1052por Abiola, Odeyinka, Abayomi-Alli, Adebayo, Tale, Oluwasefunmi Arogundade, Misra, Sanjay, Abayomi-Alli, Olusola“…Topic modelling was done with Latent Dirichlet Allocation and visualized with Multidimensional scaling. …”
Publicado 2023
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1053“…We show the effectiveness of this approach using Latent Dirichlet Allocation (LDA), and demonstrate the ability of TND to improve the quality of LDA topics in noisy document collections. …”
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1054“…We performed a topic modeling analysis using the Latent Dirichlet Allocation (LDA), and verified that most of the collected tweets were related to grocery-shopping demands or experiences. …”
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1055“…Topic modeling using latent Dirichlet allocation (LDA) was used to examine major topics discussed in water pipe–related posts before and during the pandemic. …”
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1056“…This case study employed Latent Dirichlet Allocation (LDA) topic modeling, Bidirectional Encoder Representations from Transformers (BERT) emotion analysis, and human textual analysis and examined 180,128 tweets scraped by Twitter Application Programming Interface’s (API) keyword function from January 2020 to June 2021. …”
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1057por Ritschl, Valentin, Sperl, Lisa, Andrews, Margaret Renn, Björk, Mathilda, Boström, Carina, Cappon, Jeannette, Davergne, Thomas, de la Torre-Aboki, Jenny, de Thurah, Annette, Domján, Andrea, Dragoi, Razvan Gabriel, Estévez-López, Fernando, Ferreira, Ricardo J O, Fragoulis, George E, Grygielska, Jolanta, Kõrve, Katti, Kukkurainen, Marja Leena, Madelaine-Bonjour, Christel, Marques, Andréa, Meesters, Jorit, Moe, Rikke Helene, Moholt, Ellen, Mosor, Erika, Naimer-Stach, Claudia, Ndosi, Mwidimi, Pchelnikova, Polina, Primdahl, Jette, Putrik, Polina, Rausch Osthoff, Anne-Kathrin, Smucrova, Hana, Testa, Marco, van Bodegom-Vos, Leti, Peter, Wilfred F, Zangi, Heidi A, Zimba, Olena, Vliet Vlieland, Theodora P M, Stamm, Tanja A“…We used natural language processing and the Latent Dirichlet Allocation to analyse the qualitative experiences of the participants as well as descriptive statistics and multiple logistic regression to determine factors influencing postgraduate educational readiness. …”
Publicado 2023
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1058por Howard, Brian E., Phillips, Jason, Miller, Kyle, Tandon, Arpit, Mav, Deepak, Shah, Mihir R., Holmgren, Stephanie, Pelch, Katherine E., Walker, Vickie, Rooney, Andrew A., Macleod, Malcolm, Shah, Ruchir R., Thayer, Kristina“…The remaining references were then ranked for relevance using an algorithm that considers term frequency and latent Dirichlet allocation (LDA) topic modeling. This ranking was evaluated with respect to (1) the number of studies screened in order to identify 95 % of known relevant studies and (2) the “Work Saved over Sampling” (WSS) performance metric. …”
Publicado 2016
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1059por Carron-Arthur, Bradley, Reynolds, Julia, Bennett, Kylie, Bennett, Anthony, Griffiths, Kathleen M.“…METHODS: A topic model was computed for all posts (N = 131,004) in the ISG BlueBoard using Latent Dirichlet Allocation. A model containing 25 topics was selected on the basis of intelligibility as determined by diagnostic metrics and qualitative investigation. …”
Publicado 2016
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1060por Smith, Robert J, Crutchley, Patrick, Schwartz, H Andrew, Ungar, Lyle, Shofer, Frances, Padrez, Kevin A, Merchant, Raina M“…For each participant, the total content of Facebook posts was extracted. Using the latent Dirichlet allocation natural language processing technique, Facebook language topics were correlated with frequency of Facebook use. …”
Publicado 2017
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