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Li-Na Wang, Guoqiang Zhong, Yaxin Shi and Mohamed Cheriet
Most of the dimensionality reduction algorithms assume that data are independent and identically distributed (i.i.d.). In real-world applications, however, sometimes there exist relationships between data. Some relational learning methods have been propo...
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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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Abdullah Y. Muaad, Hanumanthappa Jayappa, Mugahed A. Al-antari and Sungyoung Lee
Arabic text classification is a process to simultaneously categorize the different contextual Arabic contents into a proper category. In this paper, a novel deep learning Arabic text computer-aided recognition (ArCAR) is proposed to represent and recogni...
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Catherine Mpolokeng Sephapo
Pág. 310 - 319
Understanding the consumer?s behaviour is not an easy task; consumers are different and react differently to stimuli. Other factors may influence the consumers? final decision to purchase a product offering however, literature does not reveal extensive s...
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John T. Murphy, Jonathan Ozik, Nicholson T. Collier, Mark Altaweel, Richard B. Lammers, Andrew Kliskey, Lilian Alessa, Drew Cason and Paula Williams
Natural language processing (NLP) and named entity recognition (NER) techniques are applied to collections of newspaper articles from four cities in the U.S. Southwest. The results are used to generate a network of water management institutions that refl...
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