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Algorithms
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Análisis Temático
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Asignación Latente de Dirichlet
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Biología molecular
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Latent Dirichlet Allocation
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Topic evolution
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621por Ejegbavwo, Otega A., Berseneva, Anna A., Martin, Corey R., Leith, Gabrielle A., Pandey, Shubham, Brandt, Amy J., Park, Kyoung Chul, Mathur, Abhijai, Farzandh, Sharfa, Klepov, Vladislav V., Heiser, Brittany J., Chandrashekhar, Mvs, Karakalos, Stavros G., Smith, Mark D., Phillpot, Simon R., Garashchuk, Sophya, Chen, Donna A., Shustova, Natalia B.“…The results of Bader charge analysis and studies employing the Voronoi–Dirichlet partition of crystal structures are also presented. …”
Publicado 2020
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622por Uhanov, Andrei S., Sokolova, Marina N., Fedoseev, Aleksandr M., Bessonov, Alexei A., Nechaeva, Olga N., Savchenkov, Anton V., Pushkin, Denis V.“…Using the method of molecular Voronoi–Dirichlet polyhedra, the contributions of various types of noncovalent interactions into the formation of supramolecular structures of the obtained complexes were characterized. …”
Publicado 2021
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623por Durham, Timothy J., Daza, Riza M., Gevirtzman, Louis, Cusanovich, Darren A., Bolonduro, Olubusayo, Noble, William Stafford, Shendure, Jay, Waterston, Robert H.“…By using a novel implementation of the latent Dirichlet allocation algorithm, we identify 37 clusters of cells that correspond to different cell types in the worm, providing new maps of putative cell type–specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation.…”
Publicado 2021
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624Publicado 2020“…NLP models including Latent Dirichlet allocation (LDA), sentiment analysis (SA) and social network analysis (SNA) were applied for the analysis of the tweets and identification of topics. …”
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625“…We computed word frequencies, centralities, and latent Dirichlet allocation (LDA) topic modeling. The words like symptom, hospital and treatment ranked as the most frequently used words, and the word my appeared to have the highest centrality. …”
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626“…The corpus analysis was carried out by applying the lexical study of Natural Language Processing (NLP) through its Latent Dirichlet Allocation (LDA) tool to find out the general patterns or topics in the print media of both countries. …”
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627“…To increase the specificity of the investigation, the Latent Dirichlet allocation (LDA) topic modeling method was applied. …”
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628“…Using online hotel reviews, this study explores the difference between the influencing factors of customer satisfaction before and after the COVID-19 outbreak. By use of Latent Dirichlet Allocation and sentiment analysis, factors that affect customer satisfaction and their emotional strength before and after the COVID-19 outbreak are extracted. …”
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629“…In this study, using a COVID-19-related dataset collected with the Twitter IDs, we conduct topic and sentiment analysis from the perspective of occupation, by leveraging Latent Dirichlet Allocation (LDA) topic modeling and Valence Aware Dictionary and sEntiment Reasoning (VADER) model, respectively. …”
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630“…This study used the Latent Dirichlet Allocation (LDA) topic model to analyze pre-service teachers’ views on the nature of science (NOS). …”
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631“…Based on 38,457 physicians' profiles from a popular online healthcare community in China, we used Latent Dirichlet Allocation model, which is a common topic model, to analyze the non-English text to obtain more doctor's latent characteristics. …”
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632“…In order to draw lessons from the accident and realize knowledge sharing and reuse, this paper uses text mining technology to analyze the data of 500 construction accident investigation reports in Shenzhen, China. Firstly, a Latent Dirichlet Allocation (LDA) topic model is used to identify the unsafe behavior of construction workers and its influencing factors. …”
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633por Zhang, Xu, Liu, Yiwei, Wang, Yaming, Zhang, Liang, Feng, Lin, Jin, Bo, Zhang, Hongzhe“…Third, based on the Dirichlet distribution and information entropy measurement, a sample difficulty discrimination module is designed to assign samples with different learning difficulty levels to the aforementioned classifiers. …”
Publicado 2022
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634“…The collected answers were categorized into a variety of topics using a Latent Dirichlet Allocation based model. Consequently, the students’, teachers’ and parents’ answers were analyzed separately to obtain a general landscape of the perceptions of the education system. …”
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635“…Also, findings from the non-parametric Bayesian application (ANOVA/linear Dependent Dirichlet Process (DDP) mixture model) show how economic growth operates as a converging energy consumption-enabler over the long-run, from which the EU membership cannot be excluded. …”
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636“…While we were able to derive/access concerns/needs/questions of patients with CF, we observed challenges and issues with the traditional techniques of topic modeling, e.g., Latent Dirichlet Allocation (LDA), for fulfilling the task of topic extraction. …”
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637“…Topic modeling using the Latent Dirichlet Allocation (LDA) model was performed to examine the topics on waterpipe tobacco. …”
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638“…In addition, the Latent Dirichlet Allocation (LDA) topic model and K-Means clustering model are constructed to analyze the content of food safety policies and identify hot topics. …”
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639por Azizi, Faezeh, Hajiabadi, Hamideh, Vahdat-Nejad, Hamed, Khosravi, Mohammad Hossein“…Then, by using the statistical algorithm of Latent Dirichlet Allocation, the main topics of the tweets are identified. …”
Publicado 2023
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640por Upadhyay, Himanshu, Simsekler, Mecit Can Emre, Maalouf, Maher, Anwar, Siddiq, Omar, Mohammed“…The proposed framework utilizes Latent Dirichlet Allocation (LDA) for topic modeling to evaluate the patterns in job postings in the US and the UK. …”
Publicado 2023
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