开课单位--国立成功大学
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RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation[RETAGN:用于整体顺序推荐的关系时态注意图神经网络]
  Cheng Hsu(国立成功大学) RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation
热度:55

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UP-Growth: An Efficient Algorithm for High Utility Itemset Mining[经济增长:高实用项集挖掘算法]
  Cheng-Wei Wu(国立成功大学) Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. Although a number of re...
热度:43
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