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Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

2019

Physical Sciences and Mathematics

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Deep learning

University of South Carolina

Articles 1 - 3 of 3

Full-Text Articles in Engineering

A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Lin, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu Aug 2019

A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Lin, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu

Faculty Publications

With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and …


A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianhun Hu Aug 2019

A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianhun Hu

Faculty Publications

With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and …


Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu May 2019

Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu

Faculty Publications

Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available …