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首页> 外文会议>2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications >Context and Short Term User Intention Aware Hybrid Session Based Recommendation System
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Context and Short Term User Intention Aware Hybrid Session Based Recommendation System

机译：基于上下文和短期用户意图感知的基于混合会话的推荐系统

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摘要

Information overloading in e-commerce hinders the consumers' ability to make the right decisions. Customers visiting e-commerce websites can have specific goals in an individual session. However, using sessions that are based on the last item viewed or purchased is not enough to exploit the sessions specific intention or predict users' next actions in the sessions. In this paper, we proposed context and short term user intention aware (CSUI) framework which is based on item similarity collaborative filtering and Association Rule Session-based recommendation systems, the proposed model combines context factor of users' session and users' short term intentions. The developed model has been evaluated on two real-world datasets. Experimental results showed that using session context and users' short term intentions during the recommendation process could help in improving the accuracy of the next item prerlietion.
机译：电子商务中的信息超载阻碍了消费者做出正确决策的能力。访问电子商务网站的客户可以在单个会话中制定特定目标。但是，使用基于最后查看或购买的商品的会话不足以利用会话的特定意图或预测会话中用户的下一步操作。在本文中，我们提出了基于项目相似性协同过滤和基于关联规则会话的推荐系统的上下文和短期用户意图感知（CSUI）框架，该模型结合了用户会话的上下文因素和用户的短期意图。 。已在两个真实的数据集上评估了开发的模型。实验结果表明，在推荐过程中使用会话上下文和用户的短期意图可以帮助提高下一个项目的准确性。

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