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Christie I. Ezeife and Hemni Karlapalepu
E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems? accuracy can be improved if complex sequential patterns of user purchase behavior ar...
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Jing Tian, Zilin Zhao and Zhiming Ding
With the widespread use of the location-based social networks (LBSNs), the next point-of-interest (POI) recommendation has become an essential service, which aims to understand the user?s check-in behavior at the current moment by analyzing and mining th...
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Elham Azizi and Loutfouz Zaman
According to the American Humane Association, millions of cats and dogs are lost yearly. Only a few thousand of them are found and returned home. In this work, we use deep learning to help expedite the procedure of finding lost cats and dogs, for which a...
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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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Shuli Wang, Xuewen Li, Xiaomeng Kou, Jin Zhang, Shaojie Zheng, Jinlong Wang and Jibing Gong
Predicting users? next behavior through learning users? preferences according to the users? historical behaviors is known as sequential recommendation. In this task, learning sequence representation by modeling the pairwise relationship between items in ...
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Jie Yu, Chenle Pan, Yaliu Li and Junwei Wang
Academic text recommendation, as a kind of text recommendation, has a wide range of application prospects. Predicting texts of interest to scholars in different fields based on anonymous sessions is a challenging problem. However, the existing session-ba...
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Chunyang Liu, Jiping Liu, Jian Wang, Shenghua Xu, Houzeng Han and Yang Chen
Point-of-interest (POI) recommendation is one of the fundamental tasks for location-based social networks (LBSNs). Some existing methods are mostly based on collaborative filtering (CF), Markov chain (MC) and recurrent neural network (RNN). However, it i...
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