|
|
|
|
|
Atefeh Torkaman, Kambiz Badie, Afshin Salajegheh, Mohammad Hadi Bokaei and Seyed Farshad Fatemi Ardestani
Over the years, detecting stable communities in a complex network has been a major challenge in network science. The global and local structures help to detect communities from different perspectives. However, previous methods based on them suffer from h...
ver más
|
|
|
|
|
|
|
|
|
Panagiotis Skondras, Nikos Zotos, Dimitris Lagios, Panagiotis Zervas, Konstantinos C. Giotopoulos and Giannis Tzimas
This article presents a study on the multi-class classification of job postings using machine learning algorithms. With the growth of online job platforms, there has been an influx of labor market data. Machine learning, particularly NLP, is increasingly...
ver más
|
|
|
|
|
|
|
|
|
José Manuel Oliveira and Patrícia Ramos
Global models have been developed to tackle the challenge of forecasting sets of series that are related or share similarities, but they have not been developed for heterogeneous datasets. Various methods of partitioning by relatedness have been introduc...
ver más
|
|
|
|
|
|
|
|
|
Yilong Wu, Yingjie Chen, Rongyu Zhang, Zhenfei Cui, Xinyi Liu, Jiayi Zhang, Meizhen Wang and Yong Wu
With the proliferation and development of social media platforms, social media data have become an important source for acquiring spatiotemporal information on various urban events. Providing accurate spatiotemporal information for events contributes to ...
ver más
|
|
|
|
|
|
|
|
|
Konstantinos V. Kostas and Maria Manousaridou
In this work, supervised Machine Learning (ML) techniques were employed to solve the forward and inverse problems of airfoil and hydrofoil design. The forward problem pertains to the prediction of a foil?s aerodynamic or hydrodynamic performance given it...
ver más
|
|
|
|