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Zhan Wang, Soyeon Kim and Inwhee Joe
The Korean e-commerce market represents a large percentage of the global retail distribution market, a market that continues to grow each year, and online payments are rapidly becoming a mainstream payment method. As e-commerce becomes more active, many ...
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Yi Liu, Chengyu Yin, Jingwei Li, Fang Wang and Senzhang Wang
Accurately predicting user?item interactions is critically important in many real applications, including recommender systems and user behavior analysis in social networks. One major drawback of existing studies is that they generally directly analyze th...
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Yuna Shin, Taekgeun Kim, Seoksu Hong, Seulbi Lee, EunJi Lee, SeungWoo Hong, ChangSik Lee, TaeYeon Kim, Man Sik Park, Jungsu Park and Tae-Young Heo
Many studies have attempted to predict chlorophyll-a concentrations using multiple regression models and validating them with a hold-out technique. In this study commonly used machine learning models, such as Support Vector Regression, Bagging, Random Fo...
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Fengzhen Sun, Shaojie Li, Shaohua Wang, Qingjun Liu and Lixin Zhou
Predicting the futures from previous spatiotemporal data remains a challenging topic. There have been many previous works on predictive learning. However, mainstream models suffer from huge memory usage or the gradient vanishing problem. Enlightened by t...
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