基于关联规则和蚁群算法的基于属性的服务推荐方案

Zhikui Chen, Zhuang Shao, Zhijiang Xie, Xiaodi Huang
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引用次数: 8

摘要

随着移动商务的快速发展,预测用户的导航并进行服务推荐变得越来越重要。大多数研究都集中在使用上下文历史和用户偏好来预测用户的导航。但是,忽略了服务属性的影响。同时,有些属性是可变的,因此建议是可变的。因此,本文提出了一种基于CASUP(考虑用户偏好的上下文感知系统)的基于属性的服务推荐方案。该方法将服务划分为多个服务集群,采用Apriori算法和蚁群算法进行服务推荐。最后,通过多个仿真实验验证了该模型的有效性,验证了服务属性在移动商务中的作用。
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An attribute-based scheme for service recommendation using association rules and ant colony algorithm
With the rapid development of m-commerce, predicting user's navigation and making the service recommendation become more and more important. Most researches focus on predicting user's navigation using context history and user preferences. But, the influence of the attributes of a service has been ignored. Simultaneously, some attributes are variable, so the recommendations are changeable. Therefore, the paper proposes an attribute-based scheme for service recommendation based on CASUP (context-aware system considering user preference). In proposed approach, the services are classified into several service clusters, and the service recommendations are carried out using Apriori algorithm and ant colony algorithm. Finally, the proposed model is validated by several simulation experiments, which demonstrate the effects of the service attributes in m-commerce.
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