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Jiafeng Li, Chenhao Li, Jihong Liu, Jing Zhang, Li Zhuo and Meng Wang
With the explosive growth of mobile videos, helping users quickly and effectively find mobile videos of interest and further provide personalized recommendation services are the developing trends of mobile video applications. Mobile videos are characteri...
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Xueying Wang, Yanheng Liu, Xu Zhou, Zhaoqi Leng and Xican Wang
The next point-of-interest (POI) recommendation is one of the most essential applications in location-based social networks (LBSNs). Its main goal is to research the sequential patterns of user check-in activities and then predict a user?s next destinati...
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Mohammad Lavasani, Md Sakoat Hossan, Hamidreza Asgari, Xia Jin
Pág. 2330 - 2343
Revealed preference (RP) and stated preference (SP) data have been widely used in transportation studies to understand user's preferences regarding various travel decisions. This paper focuses on investigating the modeling techniques to address various i...
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Vilayanur V. Viswanathan, Alasdair J. Crawford, Edwin C. Thomsen, Nimat Shamim, Guosheng Li, Qian Huang and David M. Reed
An extensive review of modeling approaches used to simulate vanadium redox flow battery (VRFB) performance is conducted in this study. Material development is reviewed, and opportunities for additional development identified. Various crossover mechanisms...
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Wenkai Ni, Yanhui Du, Xingbang Ma and Haibin Lv
One of the five types of Internet information service recommendation technologies is the personalized recommendation algorithm, and knowledge graphs are frequently used in these algorithms. RippleNet is a personalized recommendation model based on knowle...
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Jiping Liu, Zhiran Zhang, Chunyang Liu, Agen Qiu and Fuhao Zhang
With the rapid development of location-based social networks (LBSNs), because human behaviors exhibit specific distribution patterns, personalized geo-social recommendation has played a significant role for LBSNs. In addition to user preference and socia...
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Mohamed Hamada and Mohammed Hassan
Recommender systems are powerful online tools that help to overcome problems of information overload. They make personalized recommendations to online users using various data mining and filtering techniques. However, most of the existing recommender sys...
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