ABCPRec: Adaptively Bridging Consumer and Producer Roles for User-Generated Content Recommendation
ABCPRec: Adaptively Bridging Consumer and Producer Roles for User-Generated Content Recommendation
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ABCPRec：为用户生成的内容推荐自适应地桥接消费者和生产者角色
DOI：
10.1145/3331184.3331335
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Masataka Goto
中科院分区：
文献类型：
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作者：
Kosetsu Tsukuda;Satoru Fukayama;Masataka Goto
在处理用户生成内容（UGC）的Web服务中，用户可以有两个角色：消费者角色和生产者角色。由于大多数商品推荐模型只考虑了用户作为消费者的角色，因此如何利用这两个角色来提高UGC推荐的准确性还没有得到充分的探讨。本文基于最先进的UGC推荐方法CPRec (consumer and producer based recommendation)，提出了ABCPRec （adapadaptive bridging CPRec）。与CPRec假设用户的两个角色总是相互关联的不同，ABCPRec根据其作为消费者的性质和作为生产者的性质之间的相似性，自适应地将两个角色连接起来。这使模型能够了解每个用户作为消费者和生产者的特征，并更准确地向每个用户推荐商品。通过使用两个真实世界的数据集，我们发现我们提出的方法在AUC方面明显优于比较方法。
In Web services dealing with user-generated content (UGC), a user can have two roles: a role of a consumer and that of a producer. Since most item recommendation models have only considered the role of a user as a consumer, how to leverage the two roles to improve UGC recommendation accuracy has been underexplored. In this paper, based on the state-of-the-art UGC recommendation method called CPRec (consumer and producer based recommendation), we propose ABCPRec (adaptively bridging CPRec). Unlike CPRec, which assumes that the two roles of a user are always related to each other, ABCPRec adaptively bridges the two roles according to the similarity between her nature as a consumer and that as a producer. This enables the model to learn each user's characteristics as both a consumer and a producer and to recommend items to each user more accurately. By using two real-world datasets, we showed that our proposed method significantly outperformed comparative methods in terms of AUC.