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Algorithms
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Algoritmos
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Análisis Temático
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Análisis de Fourier
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Análisis funcional
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Asignación Latente de Dirichlet
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Biología molecular
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Digital Documents
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Documentos Digitales
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Evolución temática
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Igualdad de género
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Inteligencia artificial
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LDA
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Latent Dirichlet Allocation
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Medios de comunicación social
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Redes sociales
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SCOPUS
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Social media
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Social networks
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Teoría algebraica de los números
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Thematic Analysis
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Topic evolution
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1061por Tapi Nzali, Mike Donald, Bringay, Sandra, Lavergne, Christian, Mollevi, Caroline, Opitz, Thomas“…METHODS: First, we applied a classic text mining technique, latent Dirichlet allocation (LDA), to detect the different topics discussed on social media dealing with breast cancer. …”
Publicado 2017
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1062“…Finally, we extracted trending topics from each of these widely used drugs’ tweets using latent Dirichlet allocation (LDA). RESULTS: Our proposed classifier obtained an F(1) score of 0.82, which significantly outperformed the two benchmark classifiers (ie, P<.001 with the lexicon-based and P=.048 with the 1-gram term frequency [TF]). …”
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1063“…Analyses were performed based on the Dirichlet-Multinomial distribution to compare group mean relative taxonomic abundances; Simpson and Shannon diversity indices were compared among groups longitudinally. …”
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1064por Biswas, Kristi, Cavubati, Raewyn, Gunaratna, Shan, Hoggard, Michael, Waldvogel-Thurlow, Sharon, Hong, Jiwon, Chang, Kevin, Wagner Mackenzie, Brett, Taylor, Michael W., Douglas, Richard G.“…CRS patients clustered into two distinct microbial subgroups using probabilistic modelling Dirichlet (DC) multinomial mixtures. DC1 exhibited significantly reduced bacterial diversity and increased dispersion and was dominated by Pseudomonas, Haemophilus, and Achromobacter. …”
Publicado 2019
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1065“…After completing natural language processing of the Korean language, a morphological analyzer, we performed topic modeling using latent Dirichlet allocation (LDA) in the Python library, Gensim. …”
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1066“…METHODS: The machine learning (ML) framework and Latent Dirichlet Allocation (LDA) topic modeling tool were used to collect and analyze behavioral data on EE. …”
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1067por Bi, Qiqing, Shen, Lining, Evans, Richard, Zhang, Zhiguo, Wang, Shimin, Dai, Wei, Liu, Cui“…Term frequency–inverse document frequency, latent dirichlet allocation models, and naive Bayes were employed to mine the various topic categories. …”
Publicado 2020
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1068“…METHODS: This article was based on the Latent Dirichlet Allocation (LDA) topic model. From a third-party platform-based B2C online pharmacy and a proprietary B2C online pharmacy (JD Pharmacy and J1.COM, respectively), 136,630 pieces of over-the-counter (OTC) drug review data posted from January 1, 2015 to December 31, 2018 were selected as samples and used to explore the satisfaction factors of B2C online pharmacy consumers regarding the entire drug purchasing process. …”
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1069por Vokó, Zoltán, Bitter, István, Mersich, Beatrix, Réthelyi, János, Molnár, Anett, Pitter, János G., Götze, Árpád, Horváth, Margit, Kóczián, Kristóf, Fonticoli, Laura, Lelli, Filippo, Németh, Bertalan“…For the second approach, we elicited Dirichlet prior distributions by three clinical experts. …”
Publicado 2020
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1070por Xue, Jia, Chen, Junxiang, Hu, Ran, Chen, Chen, Zheng, Chengda, Su, Yue, Zhu, Tingshao“…We used a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigrams and bigrams, salient topics and themes, and sentiments in the collected tweets. …”
Publicado 2020
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1071“…Using perturbation theory and the Green’s function for Laplace’s equation in 2D with Dirichlet boundary conditions, we obtain integrals for the horizontal and vertical components of the wave-induced wind in a frame of reference moving with the wave. …”
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1072por Borakati, Aditya“…Qualitative data were analysed using text mining with most frequent words, sentiment analysis with the AFINN-111 and syuzhet lexicons and topic modelling using the Latent Dirichlet Allocation (LDA). RESULTS: One thousand six hundred and eleventh collaborators from 24 countries completed the e-learning course; 1396 (86.7%) were medical students; 1067 (66.2%) entered feedback. 1031 (96.6%) rated the quality of the course a 4/5 or higher (mean 4.56; SD 0.58). …”
Publicado 2021
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1073“…Following standard preprocessing steps, we use topic modeling with Latent Dirichlet allocation (LDA) to cluster the abstracts following a minimization algorithm. …”
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1074por Bersanelli, Matteo, Travaglino, Erica, Meggendorfer, Manja, Matteuzzi, Tommaso, Sala, Claudia, Mosca, Ettore, Chiereghin, Chiara, Di Nanni, Noemi, Gnocchi, Matteo, Zampini, Matteo, Rossi, Marianna, Maggioni, Giulia, Termanini, Alberto, Angelucci, Emanuele, Bernardi, Massimo, Borin, Lorenza, Bruno, Benedetto, Bonifazi, Francesca, Santini, Valeria, Bacigalupo, Andrea, Voso, Maria Teresa, Oliva, Esther, Riva, Marta, Ubezio, Marta, Morabito, Lucio, Campagna, Alessia, Saitta, Claudia, Savevski, Victor, Giampieri, Enrico, Remondini, Daniel, Passamonti, Francesco, Ciceri, Fabio, Bolli, Niccolò, Rambaldi, Alessandro, Kern, Wolfgang, Kordasti, Shahram, Sole, Francesc, Palomo, Laura, Sanz, Guillermo, Santoro, Armando, Platzbecker, Uwe, Fenaux, Pierre, Milanesi, Luciano, Haferlach, Torsten, Castellani, Gastone, Della Porta, Matteo G.“…Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. …”
Publicado 2021
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1075“…Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. …”
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1076“…To analyze these threads, we applied top-down and bottom-up language analysis methods based on topic modeling with latent Dirichlet allocation and 13 indicators from the Linguistic Inquiry and Word Count program, respectively. …”
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1077“…To better understand the public opinion, we used latent Dirichlet allocation to extract topics and investigate how tweet contents are related to people’s attitude. …”
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1078“…The main topics in tweets were extracted by latent Dirichlet allocation analysis. RESULTS: We collected 2,678,372 tweets related to COVID-19 vaccines from 841,978 unique users and annotated 5000 tweets. …”
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1079por Cao, Guang, Shen, Lining, Evans, Richard, Zhang, Zhiguo, Bi, Qiqing, Huang, Wenjing, Yao, Rui, Zhang, Wenli“…In this study, the Ortony, Clore, and Collins (OCC) model, Word2Vec, and Bi-directional Long Short-Term Memory model were employed to determine emotional types, train vectorization of words, and identify each text emotion for the training set. Latent Dirichlet Allocation models were also employed to mine the various topic categories, while topic emotional evolution was visualized. …”
Publicado 2021
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1080“…Tweet content was analyzed for sentiment and topic, using Latent Dirichlet Allocation. We used social network analysis to examine the degree to which identified topics are siloed within specific groups or disseminated through the broader T1D web-based community. …”
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