2022
DOI: 10.1016/j.eswa.2022.118119
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Aspect2Labels: A novelistic decision support system for higher educational institutions by using multi-layer topic modelling approach

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Cited by 19 publications
(10 citation statements)
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“…The three categories into which sentiment analysis can be divided are the machine learning technique, the lexicon-based approach, and the hybrid strategy that combines the previous two approaches [10]. Nowadays, computational technologies are being used in various domains of life, including healthcare [14], security [15] [21] [25] and also in safety purposes [16], disaster [17], and situational awareness [19] [26] [27] in the educational domain [18] as well. Sentiment analysis is a prominent research topic in demand under the category of NLP [20].…”
Section: Literature Reviewmentioning
confidence: 99%
“…The three categories into which sentiment analysis can be divided are the machine learning technique, the lexicon-based approach, and the hybrid strategy that combines the previous two approaches [10]. Nowadays, computational technologies are being used in various domains of life, including healthcare [14], security [15] [21] [25] and also in safety purposes [16], disaster [17], and situational awareness [19] [26] [27] in the educational domain [18] as well. Sentiment analysis is a prominent research topic in demand under the category of NLP [20].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Currently, every well-known organization uses data mining and machine learning applications frequently to explore the meaningful hidden patterns from raw collected data [17][18][19]. Nowadays, machine learning is used in various aspects of life [20] to perform complex analyses and explore hidden patterns from data points [21]. The authors of [5] calculated the distance between each unique landmark and a nose peak to capture the changes.…”
Section: A Local Binary Pattern Approachmentioning
confidence: 99%
“…Due to a lack of global generalization, these models can not imagine possible problems and provide solutions. To overcome these limitations, in this work, we proposed three pretrained models, which are Resnet-50, Vgg-16, and inception-V3 [3,5,[15][16][17][18][19][20] II. RELATED WORK Here we will review some work on the local binary patterns approach for feature extraction.…”
Section: Introductionmentioning
confidence: 99%
“…After applying the transfer learning technique, the accuracy of the three pre-trained models, including ResNet-50, Inception V3, and VGG-16, is 98%, 97%, and 98%, respectively. Apart from healthcare, machine learning (Tang et al, 2022) is also used in various fields (Wahid et al, 2021) and also in various domains of life (Zhao et al, 2022) (Ayoub et al, 2022). The authors' proposed system optimizes treatment and prevents severe kidney stone illness, and they obtained 0.86 sensitivity using a 3D U-Net model.…”
Section: Introductionmentioning
confidence: 99%
“…The authors' proposed system optimizes treatment and prevents severe kidney stone illness, and they obtained 0.86 sensitivity using a 3D U-Net model. A spherical multi-output Gaussian process may be implemented to model and monitor the 3D surfaces of stones (Hussain et al, 2022). By studying the literature, we observed that the rapid creation of crucial tools for medical diagnostics is being fueled by artificial intelligence (AI), which is quickly becoming a crucial concept in medicine (Wong et al, 2020) (Wei et al, 2017).…”
Section: Introductionmentioning
confidence: 99%