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Making tourist guidance systems more intelligent, adaptive and personalised using crowd sourced movement data

机译:利用来自人群的运动数据,使导游系统更加智能,自适应和个性化

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摘要

Ambient intelligence (AmI) provides adaptive, personalized, intelligent, ubiquitous and interactive services to wide range of users. AmI can have a variety of applications, including smart shops, health care, smart home, assisted living, and location-based services. Tourist guidance is one of the applications where AmI can have a great contribution to the quality of the service, as the tourists, who may not be very familiar with the visiting site, need a location-aware, ubiquitous, personalised and informative service. Such services should be able to understand the preferences of the users without requiring the users to specify them, predict their interests, and provide relevant and tailored services in the most appropriate way, including audio, visual, and haptic. This paper shows the use of crowd sourced trajectory data in the detection of points of interests and providing ambient tourist guidance based on the patterns recognised over such data.
机译:环境智能(AmI)为广泛的用户提供自适应,个性化,智能,无处不在和交互式服务。 AmI可以具有多种应用程序,包括智能商店,医疗保健,智能家居,辅助生活和基于位置的服务。旅游指南是AmI可以对服务质量做出重大贡献的应用程序之一,因为可能对访问站点不太熟悉的游客需要位置感知,无处不在,个性化和信息化的服务。这样的服务应该能够理解用户的偏好,而无需用户指定他们的偏好,预测他们的兴趣,并以最合适的方式(包括音频,视觉和触觉)提供相关的量身定制的服务。本文展示了使用人群来源的轨迹数据来检测兴趣点并基于在这些数据上识别的模式来提供周围游客的指导。

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