Data clustering: application and trends
Clustering has primarily been used as an analytical technique to group unlabeled data for
extracting meaningful information. The fact that no clustering algorithm can solve all …
extracting meaningful information. The fact that no clustering algorithm can solve all …
Toward neurosubtypes in autism
There is a consensus that substantial heterogeneity underlies the neurobiology of autism
spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of …
spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of …
Clustering algorithms: A comparative approach
Many real-world systems can be studied in terms of pattern recognition tasks, so that proper
use (and understanding) of machine learning methods in practical applications becomes …
use (and understanding) of machine learning methods in practical applications becomes …
Survey of state-of-the-art mixed data clustering algorithms
Mixed data comprises both numeric and categorical features, and mixed datasets occur
frequently in many domains, such as health, finance, and marketing. Clustering is often …
frequently in many domains, such as health, finance, and marketing. Clustering is often …
A proactive crash risk prediction framework for lane-changing behavior incorporating individual driving styles
Y Zhang, Y Chen, X Gu, NN Sze, J Huang - Accident Analysis & Prevention, 2023 - Elsevier
Driving style may have an important effect on traffic safety. Proactive crash risk prediction for
lane-changing behaviors incorporating individual driving styles can help drivers make safe …
lane-changing behaviors incorporating individual driving styles can help drivers make safe …
[LIBRO][B] Text data mining
With the rapid development and popularization of Internet and mobile communication
technologies, text data mining has attracted much attention. In particular, with the wide use …
technologies, text data mining has attracted much attention. In particular, with the wide use …
Stgnnks: identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering
Background: Spatial transcriptomics technologies fully utilize spatial location information,
tissue morphological features, and transcriptional profiles. Integrating these data can greatly …
tissue morphological features, and transcriptional profiles. Integrating these data can greatly …
[HTML][HTML] Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover,
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …
The MuSe 2021 multimodal sentiment analysis challenge: sentiment, emotion, physiological-emotion, and stress
Multimodal Sentiment Analysis (MuSe) 2021 is a challenge focusing on the tasks of
sentiment and emotion, as well as physiological-emotion and emotion-based stress …
sentiment and emotion, as well as physiological-emotion and emotion-based stress …
An interval‐valued composite indicator for energy efficiency and green entrepreneurship
Promoting energy‐efficient technologies can support green entrepreneurship via innovation
creation. Energy efficiency policies and practices can promote cleaner productions and …
creation. Energy efficiency policies and practices can promote cleaner productions and …