In recent years, more and more geo-labelled data are available that benefit from advanced hardware (positioning systems, environmental sensors), software (standards, tools, network services) and the ever-growing mentality of sharing (crowdsourcing for geographic tagging). Based on human activities, many daily web/app services (Facebook, Tweeter, and Foursquare) generate data and traces that are often transparently annotated with location and contextual information. Such services make it easier to collect and combine rich and diverse information about locations. Exploiting geo-labelled data provides a tremendous potential to materially improve existing and offer novel types of recommendation services. Those recommendation services bring benefits for many domains, including social networks, marketing and tourism.

中文翻译：

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位置感知计算到移动服务推荐：理论与实践

近年来，随着先进硬件（定位系统、环境传感器）、软件（标准、工具、网络服务）和不断增长的共享心态（地理标记众包）的发展，越来越多的地理标记数据可用。许多日常网络/应用程序服务（Facebook、Tweeter 和 Foursquare）基于人类活动生成数据和轨迹，这些数据和轨迹通常带有位置和上下文信息的透明注释。此类服务使收集和组合有关位置的丰富多样的信息变得更加容易。利用地理标记数据提供了巨大的潜力，可以从本质上改善现有的推荐服务并提供新型推荐服务。这些推荐服务为许多领域带来好处，包括社交网络、营销和旅游。