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A recommender system to generate museum itineraries applying augmented reality and social-sensor mining techniques
Virtual Reality ( IF 4.4 ) Pub Date : 2018-09-29 , DOI: 10.1007/s10055-018-0366-z
Miguel Torres-Ruiz , Felix Mata , Roberto Zagal , Giovanni Guzmán , Rolando Quintero , Marco Moreno-Ibarra

Nowadays, museums offer technological and digital options to enrich the user experience in a visit. However, questions arise like which exhibition/museum could I visit? How to tour it and get the best experience? These questions are not easy to answer, because they do not represent tasks straightforward. Considering that the experiences of visiting a museum are now available in social networks, in which users describe, rate, and disseminate a work of art/exhibition of a museum, this information can be mined to generate tour recommendations in museums. Such recommendations could be improved by combining and applying data mining obtained from Internet of Things sensors installed in museums. In this paper, a hybrid approach to make recommendations for museum visits is proposed. It includes an Internet of Things architecture of beacons, incorporating some technologies based on semantic analysis, data mining, and machine learning. This approach integrates and combines data sources for generating and recommending indoor and outdoor itineraries for museums, which are visualized with augmented reality. The itinerary is built, taking into consideration opinions and assessments from social networks, the semantic classification of museums, and cultural activities, as well as data measured by beacon sensors in museum exhibitions. The result is a customized tour with augmented reality that contains a set of recommendations of how to visit a set of museums and obtain a better experience of the visit. A prototype of mobile application is available in the Google Play, called the “Historic Center,” with almost 500 downloads and an acceptable evaluation.

中文翻译:

一种使用增强现实和社交传感器挖掘技术生成博物馆行程的推荐系统

如今,博物馆提供技术和数字选择,以丰富参观中的用户体验。但是,出现了一些问题,例如我可以参观哪个展览/博物馆?如何游览它并获得最佳体验?这些问题不容易回答,因为它们并不代表简单的任务。考虑到现在可以在社交网络中获得参观博物馆的经验,用户可以在其中描述,评价和传播艺术品/博物馆展览,因此可以挖掘此信息以在博物馆中生成旅游推荐。通过组合和应用从博物馆中安装的物联网传感器获得的数据挖掘,可以改进此类建议。在本文中,提出了一种为博物馆参观提供建议的混合方法。它包括信标的物联网架构,结合了基于语义分析,数据挖掘和机器学习的一些技术。这种方法集成并组合了数据源,用于生成和推荐博物馆的室内和室外行程,并通过增强现实进行可视化。行程是根据社交网络的意见和评估,博物馆的语义分类,文化活动以及博物馆展览中由信标传感器测量的数据而制定的。结果是定制的具有增强现实的游览,其中包含有关如何参观一组博物馆并获得更好的参观体验的建议。Google Play上提供了移动应用程序的原型,称为“历史中心”,下载量接近500次,评估结果令人满意。
更新日期:2018-09-29
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