Mining Spatiotemporal Data: From Personal Use to Community Knowledge

这个项目将开发数据挖掘算法，用于从基于位置的服务跟踪中提取语义位置和例程等概念，沿着处理隐私问题的技术。这些跟踪将来自一个名为PlaceMail的系统，该系统生成连接虚拟和物理世界的使用记录。PlaceMail用户创建虚拟消息（如提醒和待办事项列表），以便在特定的地点或时间在位置感知手机客户端上发送。PlaceMail还可以收集用户在某个位置和时间的存在痕迹。这些数据将使新的应用程序，如本地搜索引擎，让用户利用集体社区的意见，找到最好的地方，以获得所需的商品或服务，和一个社会匹配系统，可以把人们聚集在一起有类似的惯例，以促进乘车共享和增加社区凝聚力。算法将提取和处理信息，从位置相关的数据，包括用于从踪迹中提取更高级别的结构（如路径）的数据挖掘算法，以及将来自消息的关键字与基于踪迹的流行度估计组合以返回相关和高质量结果的联合收割机检索算法。还将开发社交匹配算法，可以找到具有相似例程的人，以及推荐算法，以建议用户可能感兴趣的新地方。隐私问题是这样一个系统的核心问题，因此该项目的一个重要项目将是设计易于使用的技术来管理它们。隐私要求将通过与PlaceMail用户的上下文原型设计进行调查，其中应用程序的早期原型使用用户自己的数据填充。这种方法将使用户更容易理解共享数据的风险和好处，从而产生可靠的要求。对应用程序的经验性评价将验证结果。算法和隐私管理技术将被纳入目标应用程序。PlaceMail的大规模实地试验（以产生足够数量的真实的数据）将与对照实验室研究相结合，将目标应用与现有的基线应用进行比较。位置感知技术可以将万维网的新虚拟世界与物理世界联系起来，该项目是开发可以聚合有用的位置相关信息的工具的重要一步。不仅人们个人会受益，例如通过找到有关其社区地点的更好信息，而且社区也可能受益于增强的凝聚力，因为公民可以从彼此的经验中学习，建立基于共同利益的关系，并更有效地使用公共资源（道路，社区中心，公园等）。该项目将与研究社区共享生成的数据集，适当匿名并征得用户同意，并将为一组研究生提供深入和多样化的培训。

This project will develop data mining algorithms for extracting concepts such as semantic locations and routines from location based service traces, along with techniques for handling privacy concerns. The traces will come from a system called PlaceMail that generates use records that link the virtual and physical worlds. PlaceMail users create virtual messages (such as reminders and to-do lists) for delivery at a specific place or time on a location-aware cell phone client. PlaceMail also can collect traces of user presence at a location and time. These data will enable novel applications such as a local search engine that lets the user tap into the collective community opinion to find the best place to obtain desired goods or services, and a social matching system that can bring together people with similar routines, to facilitate ride sharing and increase community cohesion.The algorithms will extract and process information from location-linked data, including data mining algorithms to extract higher-level constructs like paths from traces and retrieval algorithms that combine keywords from messages with popularity estimates based on traces to return relevant and high-quality results. Also to be developed will be social matching algorithms that can find people with similar routines and recommendation algorithms to suggest new places a user might be interested in.Privacy concerns are a central issue for such a system, so an important project of the project will be designing easy-to-use techniques for managing them. Privacy requirements will be investigated through contextual prototyping with PlaceMail users, in which early prototypes of the applications are filled in with the users' own data. This method will make it easy for users to conceive of the risks and benefits of sharing their data, and thus will lead to reliable requirements. Empirical evaluations of the applications will validate results. The algorithms and privacy management techniques will be incorporated into target applications. Large field trials of PlaceMail (to generate sufficient amounts of real data) will be combined with controlled laboratory studies that compare the target applications to existing baseline applications. Location-aware technologies can link the new virtual world of the World Wide Web to the physical world, and this project is a major step in the development of tools that can aggregate useful location-linked information. Not only will people benefit individually, for example by finding better information about places in their community, but also communities may benefit from increased cohesion, as citizens learn from each other's experience, establish relationships based on shared interests, and use public resources (roads, community centers, parks, and the like) more efficiently. This project will share the datasets produced with the research community, suitably anonymized and with user consent, and it will provide deep and diverse training to a set of graduate students.