“…To begin, the Latent Dirichlet Allocation (LDA) was employed to extract information about the topic of comments. …”
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“…Full associated data were downloaded in the format of PubMed and extracted in the R platform. Latent Dirichlet allocation (LDA) was adopted to identify the research topics from the abstract of each publication using Python. …”
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“…An intelligent augmentation algorithm generates meaningful fake news statements. The latent Dirichlet allocation (LDA) technique is employed for topic modelling to assign the categories to news statements. …”
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“…Full associated data were downloaded in the format of PubMed, and extracted in the R platform. Latent Dirichlet allocation (LDA) was adopted to identify the research topics from the abstract of each publication using Python. …”
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“…We developed an automated qualitative assistant (AQUA) using a semiclassical approach, replacing Latent Semantic Indexing/Latent Dirichlet Allocation with a more transparent graph-theoretic topic extraction and clustering method. …”
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“…This paper also summarizes themes and topics of tweets in our dataset using both social media exclusive tools (i.e., #hashtags, @mentions) and the latent Dirichlet allocation model. We welcome requests for data sharing and conversations for more insights. …”
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“…This paper investigates the latent topics of users’ posts/comments using Latent Dirichlet Allocation, an unsupervised machine learning approach that uncovers the thematic structure of a document collection. …”
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“…Next, we used the latent Dirichlet allocation topic model to reconfirm the panic model. …”
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“…Performance varied widely, and four methods noticeably outperformed the others: hdp (based on hierarchical Dirichlet processes), SigProExtractor (based on multiple non-negative matrix factorizations over resampled data), TCSM (based on an approach used in document topic analysis), and mutSpec.NMF (also based on non-negative matrix factorization). …”
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“…TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet process regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWASs using either individual-level or summary-level genome-wide association study (GWAS) data, and implement both burden and variance-component statistics for gene-based association tests. …”
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“…We identified the research stages based on the literature growth curve, extracted research topics using the latent Dirichlet allocation model, and analyzed topic evolution patterns by calculating the cosine similarity between topics from the adjacent stages. …”
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“…With the rapid proliferation of social networking sites (SNS), automatic topic extraction from various text messages posted on SNS are becoming an important source of information for understanding current social trends or needs. Latent Dirichlet Allocation (LDA), a probabilistic generative model, is one of the popular topic models in the area of Natural Language Processing (NLP) and has been widely used in information retrieval, topic extraction, and document analysis. …”
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“…To study the consumers’ attitude about the BDPD, this study constructed a semantic recognition frame to deconstruct the Affection-Behavior-Cognition (ABC) consumer attitude theory using machine learning models inclusive of the Labeled Latent Dirichlet Allocation (LDA), Long Short-Term Memory (LSTM), and Snow Natural Language Processing (NLP), based on social media comments text dataset. …”
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“…Data were collected from parent discussions of fussy eating on a Reddit forum (80,366 posts). Latent Dirichlet allocation was used to identify discussions of fussy eating. …”
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“…Data regarding the publication volume, international collaborations, and geographical locations were analyzed by bibliometrics analysis. Latent Dirichlet Allocation (LDA) was undertaken to categorize publications into different research topics. …”
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“…Firstly, through crawler technology and LDA (Latent Dirichlet Allocation) topic model, this article analyzes the intervention measures taken by various social forces in China to curb the spread of panic buying, and summarizes the multi-channel intervention measures including online and offline forms. …”
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“…We tackle these intriguing questions by leveraging the power of Hubbell’s unified neutral theory of biodiversity, specifically implemented as the HDP-MSN (hierarchical Dirichlet process approximated multi-site neutral model), which allows for constructing truly multi-site metacommunity models, simultaneously including vaginal and semen microbiomes. …”
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“…This study aims to provide an overview of the topics/issues of concern in the countries while responding to hydrometeorological extreme events (e.g., floods and cyclones) during the pandemic. Latent Dirichlet Allocation (LDA), a computational topic modeling technique, is employed to reduce the numerous (i.e., 1771) humanitarian reports/news to key terms and meaningful topics for 24 countries. …”
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“…Text mining was performed using latent Dirichlet allocation (LDA) on the dataset to determine associations between phrases and thus identify common themes in posts about NSSI. …”
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“…Following preprocessing to make latent variables and their dynamics transparent with latent Dirichlet allocation and a variational autoencoder, a post-hoc explanation is implemented in which a hidden Markov model and learning from an interpretation transition are combined with a long short-term memory architecture that learns sequential data between touchpoints for extracting attitude rules for CJM. …”
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