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A smart city mobile application for multitype, proactive, and context-aware recommender system

机译:适用于多类型,主动型和上下文感知推荐系统的智能城市移动应用程序

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摘要

This paper presents a design and implementation of a multitype, proactive and context-aware recommender system in the environment of Internet of Things (IoT). The main features of this recommender system includes the consideration of the context of the user in recommendation, the ability to recommend multi-types in the same applications such as Restaurant, Gas Station, Attraction... etc... Also, the proposed recommender system is proactive, where the recommendations are pushed to the user without explicit query by him/her. The system was trained and tested. Then it was developed as Android application and tested by 50 users who filled a survey. The results show that the system got an overall accuracy of 91.2%. Also, as a mobile application, the majority of the users found this application useful in daily life (92%), support smart city operation (92%), and would recommend the application for others (86%).
机译:本文提出了一种在物联网(IoT)环境中的多类型,主动和上下文感知推荐器系统的设计和实现。此推荐器系统的主要功能包括:考虑推荐中用户的上下文,在同一应用程序中推荐多种类型的功能,例如餐馆,加油站,景点...等。此外,建议的推荐器系统是主动的,在没有用户明确询问的情况下,将推荐推给用户。该系统已经过培训和测试。然后将其开发为Android应用程序,并由50位填写调查的用户进行了测试。结果表明,该系统的总体精度为91.2%。另外,作为移动应用程序,大多数用户发现此应用程序在日常生活中很有用(92%),支持智能城市运营(92%),并会推荐其他应用程序(86%)。

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