Recommendation systems are present in multiple contexts as e-commerce, websites, and media streaming services. As scenarios get more complex, techniques and tools have to consider a number of variables. When recommending services/products to mobile users while they are in indoor environments next to the object of the recommendation, variables as location, interests, route, and interaction logs also need to be taken into account. In this context, this work discusses the practical challenges inherent to the context of indoor mobile recommendation (e.g., mall, parking lot, museum, among others) grounded on a case and a systematic review. With the presented results, one expects to support practitioners in the task of defining the proper approach, technology, and notification method when recommending services/products to mobile users in indoor environments.
翻译:建议系统存在于电子商务、网站和媒体流服务等多种背景下。当情景变得更加复杂时,技术和工具必须考虑若干变量。当向移动用户推荐服务/产品时,当他们位于建议对象旁边的室内环境时,也需要考虑作为地点、兴趣、路线和互动日志的变量。在这方面,这项工作讨论室内移动建议(如商场、停车场、博物馆等)在个案和系统审查基础上所固有的实际挑战。根据所介绍的结果,人们期望在向室内环境中移动用户推荐服务/产品时,支持从业人员确定适当方法、技术和通知方法。