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Margarida Mendonça and Álvaro Figueira
As social media (SM) becomes increasingly prevalent, its impact on society is expected to grow accordingly. While SM has brought positive transformations, it has also amplified pre-existing issues such as misinformation, echo chambers, manipulation, and ...
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Chunchun Hu, Qin Liang, Nianxue Luo and Shuixiang Lu
Analysis of the spatiotemporal distribution of online public opinion topics can help understand the hotspots of public concern. The topic model is employed widely in public opinion topic clustering for social media data. In order to handle topic-clusteri...
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Ferenc Izsák and Taki Eddine Djebbar
We propose neural-network-based algorithms for the numerical solution of boundary-value problems for the Laplace equation. Such a numerical solution is inherently mesh-free, and in the approximation process, stochastic algorithms are employed. The chief ...
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Elena Quatrini, Silvia Colabianchi, Francesco Costantino and Massimo Tronci
In the field of industrial process monitoring, scholars and practitioners are increasing interest in time-varying processes, where different phases are implemented within an unknown time frame. The measurement of process parameters could inform about the...
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Gabriele Papadia, Massimo Pacella and Vincenzo Giliberti
This paper focuses on the automatic analysis of conversation transcriptions in the call center of a customer care service. The goal is to recognize topics related to problems and complaints discussed in several dialogues between customers and agents. Our...
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Gaocai Li, Mingzheng Liu, Xinyu Zhang, Chengbo Wang, Kee-hung Lai and Weihuachao Qian
Recognition and understanding of ship motion patterns have excellent application value for ship navigation and maritime supervision, i.e., route planning and maritime risk assessment. This paper proposes a semantic recognition method for ship motion patt...
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Yuexuan Zhao and Jing Huang
Graph variational auto-encoder (GVAE) is a model that combines neural networks and Bayes methods, capable of deeper exploring the influential latent features of graph reconstruction. However, several pieces of research based on GVAE employ a plain prior ...
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Monika Tanwar, Hyunseok Park and Nagarajan Raghavan
Lubricating Oil Diagnostics and Prognostics.
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Girma Neshir, Andreas Rauber and Solomon Atnafu
Topic Modeling is a statistical process, which derives the latent themes from extensive collections of text. Three approaches to topic modeling exist, namely, unsupervised, semi-supervised and supervised. In this work, we develop a supervised topic model...
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Adam Wawrzynski and Julian Szymanski
To effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such ...
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