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Sumet Darapisut, Komate Amphawan, Nutthanon Leelathakul and Sunisa Rimcharoen
Location-based recommender systems (LBRSs) have exhibited significant potential in providing personalized recommendations based on the user?s geographic location and contextual factors such as time, personal preference, and location categories. However, ...
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Jiagang Song, Jiayu Song, Xinpan Yuan, Xiao He and Xinghui Zhu
With the rapid development of Internet technology, how to mine and analyze massive amounts of network information to provide users with accurate and fast recommendation information has become a hot and difficult topic of joint research in industry and ac...
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Tan Nghia Duong, Nguyen Nam Doan, Truong Giang Do, Manh Hoang Tran, Duc Minh Nguyen and Quang Hieu Dang
Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital...
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Triyanna Widiyaningtyas, Muhammad Iqbal Ardiansyah and Teguh Bharata Adji
One of the most prevalent recommendation systems is ranking-oriented collaborative filtering which employs ranking aggregation. The collaborative filtering study recently applied the ranking aggregation that considers the weight point of items to achieve...
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Muzamil Hussain Syed, Tran Quoc Bao Huy and Sun-Tae Chung
With the rapid growth of internet data, knowledge graphs (KGs) are considered as efficient form of knowledge representation that captures the semantics of web objects. In recent years, reasoning over KG for various artificial intelligence tasks have rece...
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