关键词: 上下文感知, 关联规则, 移动应用, 相似度, 铁路客运服务

Abstract:

Aiming at the problem of how to provide efficient and personalized service for passengers of high-speed railway stations in real time, this article introduces context information into the service recommendation process, and analyzes user context information according to time, space, user, and application in four aspects. The growth algorithm enables it to support the mining of two-dimensional data items and obtain the association rules between context and service functions. Through the similarity calculation with the current context information, a personalized service set available in the current application scenario is constructed. Experiments show that this method can significantly improve the accuracy and hit rate of service matching, and help to improve passenger service satisfaction.

Key words: context-aware, association rules, mobile application, similarity, railway passenger service