Results 11 to 20 of about 1,354 (119)
ANOMALY DETECTION IN ONLINE SOCIAL MEDIA THROUGH ADVANCED AI TECHNIQUES AND TOPIC MODELING [PDF]
Proceedings on Engineering SciencesThe ubiquity of online social media platforms has led to an increasing need for effective anomaly detection methods to identify irregularities and potential threats within user-generated content.
Navdeep Bohra +4 more
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Estimating News Coverage Patterns using Latent Dirichlet Allocation (LDA)
Sukkur IBA Journal of Emerging Technologies, 2018 The growing rate of unstructured textual data has made an open challenge for the knowledge discovery, which aims extracting desired information from large collection of data.
Naeem Ahmed Mahoto
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A Text Classification Algorithm Based on Neural Network and LDA [PDF]
Jisuanji gongcheng, 2019 The traditional Latent Dirichlet Allocation(LDA) topic model uses Gibbs Sampling to fit unknown parameters under known conditional distributions in text classification calculations,making it difficult to weigh classification accuracy and computation ...
NIU Shuoshuo, CHAI Xiaoli, LI Deqi, XIE Bin
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LDA filter: A Latent Dirichlet Allocation preprocess method for Weka.
PLoS ONE, 2020 This work presents an alternative method to represent documents based on LDA (Latent Dirichlet Allocation) and how it affects to classification algorithms, in comparison to common text representation.
P Celard +3 more
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LATENT DIRICHLET ALLOCATION (LDA) METHOD ANALYSIS ABOUT COVID-19 VACCINE ON TWITTER SOCIAL MEDIA
Barekeng, 2022 Twitter is one social media that often provides much information for its users, one of which is information regarding the COVID-19 vaccination. This study aimed to explore and find out what topics are often discussed on Twitter social media. One of which
Happy Alyzhya Haay, Adi Setiawan
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Science and Technology Video Text Classification Based on Improved Labeled LDA Model [PDF]
Jisuanji gongcheng, 2018 In the process of classifying video texts in the field of science and technology,it is easy to ignore the terminology with high classification contribution.Considering the problem that the traditional Labeled Latent Dirichlet Allocation (LDA) model has ...
MA Jianhong,FAN Yuexiang
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Applied Sciences, 2021 To assess critically the scientific literature is a very challenging task; in general it requires analysing a lot of documents to define the state-of-the-art of a research field and classifying them. The documents classifier systems have tried to address
Noemi Scarpato +2 more
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Artificial Intelligence in Agriculture, 2020 Breakup patterns of agricultural formulations are explored using unsupervised learning techniques to elucidate the mechanics of atomization for oil-in-water formulations.
Hongfei Li +3 more
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Unsupervised Machine Learning to Identify Depressive Subtypes [PDF]
Healthcare Informatics Research, 2022 Objectives This study evaluated an unsupervised machine learning method, latent Dirichlet allocation (LDA), as a method for identifying subtypes of depression within symptom data. Methods Data from 18,314 depressed patients were used to create LDA models.
Benson Kung +4 more
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Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
NeuroImage: Clinical, 2018 The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific ...
Xiuchao Sui, Jagath C. Rajapakse
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