GALE: Global Accessibility to Local Experience

推荐系统已经在过去15年中产生，其目的是基于用户的个人简档、她/他作为客户/网络用户的过去历史以及甚至她/他在社交网络中的朋友社区，向个人用户推荐在互联网的虚拟空间中出现的机会。此外，Facebook等在线社交网络的兴起允许推荐系统利用新的信息源：用户社交网络。互联网接入现在正变得越来越移动的，并且智能手机正在以越来越复杂的方式改变人们与地方以及彼此之间的交互方式。智能手机开始影响用户在旅途中访问信息和接收建议的方式。更具体地说，目前正在开发创新的推荐系统，以利用基于GPS或其他位置敏感信息，通过智能手机与个人用户进行关联。这第二代推荐系统，由于是基于位置的，提出了一组完全不同的问题，这不仅与用户的知识（她或他的“简档”）有关，而且与地点有关。对地方的了解可以通过导游、教科书和旅行报告或直接经验来实现。这些方法在性质上是完全不同的。前者是全球可访问的（每个人都可以从远处获得），并且相对快速获得，特别是在互联网时代。后者只能在当地获得（需要在当地才能获得），并且是由生活在当地的人通过个人当地互动产生的，只有经过长期互动和建立相互信任的个人关系才能获得。当访问一个新的地方时，您必须仅依赖于全球信息来导航该地方并访问其资源。相反，如果你是一个当地人，你对这个地方的了解主要是通过你个人的长期交流来构建的，你的邻居每天都在做什么，他们最喜欢的地方在附近;这样一来，你不仅要依赖当地的知识，但你也会通过局部的相互作用，对形成和持续的重建做出贡献，你的邻居在他们的互动中所使用的信息的形成。如果我们将长期的、本地生成的关于地点的知识命名为“邻域知识”，我们可以说人们在当地做什么在某种程度上取决于他们对邻域知识的访问程度。第二代推荐系统允许“全球”地点用户，即访问一个地方的人对这个地方本身没有经验，获取“全球”可用信息。然而，这些系统仍然没有利用大量的信息，因为地理和社会只是以一种表面的方式“相遇”：换句话说，该系统没有利用任何关于地方“社区”过去和“目前”对地方的具体使用的信息。随着基于位置的社交网络（如foursquare或Gowalla）的病毒式扩张，邻里知识信息现在变得越来越可用，现在有可能探索第三代推荐系统，其中有关用户社区过去如何使用（历史使用）或在查询时如何使用（实时使用）的地方的知识是系统的关键要素。GALE项目背后的主要动机是开创这样的第三代推荐系统，这将使快速增长的人口的“全球”城市用户访问一定程度的信息，邻里的知识，这是固有的全球知识库无法访问，并在真实的时间。

Recommender Systems have been generated in the past 15 years with the aim to suggest to individual users opportunities arising in the virtual space of the Internet on the basis of the individual profile of the user, her/his past history as a customer/web-user and even her/his friends' community in social networks. Further, the rise of online social networks such as Facebook has allowed for a new source of information to be exploited by recommendation systems: the user social network. Internet access is now becoming increasingly mobile and smart phones are changing the way people interact with places and with each other in an increasingly complex manner. Smart phones are starting to impact the way users access information on the go and receive suggestions. More specifically, innovative recommender systems are currently being developed to exploit GPS-based or other location-sensitive information, associated on-the-go to individual users through smartphones. This second generation of recommender systems, by being location-based, pose an entirely different set of problems which not only have to do with the knowledge of the user (her or his "profile"), but also with that of the places. Knowledge of places can be achieved by means of guides, textbooks and journey reports, or by direct experience. These ways are quite different in nature. The former is globally accessible (everybody can get it from afar) and relatively fast to obtain, especially in the age of the Internet. The latter is only locally accessible (one needs to be in the place to access it) and, being generated by those living in the place through personal local interaction, it becomes accessible only after long-term interactions and the construction of personal relationship of mutual trust. When visiting a new place, you would necessarily rely only on global information to navigate the place and access its resources. Conversely, if you are a local, your knowledge of the place is mostly constructed through your personal long-term exchange with what all your neighbors are doing every day and with their favorite places in the neighborhood; as a result, you not only would rely on local knowledge, but you would also contribute - by interacting locally - to the formation and continuous re-shaping of the information used by your neighbors too in their interaction. If we name the long-term, locally generated knowledge of the place "neighborhood knowledge", we can say that what people locally do in places is in one way or another dependent on the extent to which they have access to the neighborhood knowledge.The second generation of recommender systems allows "global" place-users, i.e. people visiting a place who are not experienced with the place itself, to access "globally" available information. However, a good deal of information is still not exploited in these systems, as the geographic and the social only "meet" in a superficial way: in other words, the system does not take advantage of any information about the particular use of the place that local "communities" have done in the past and do "at the moment". As neighborhood knowledge information is now becoming increasingly available through the viral expansion of location-based social networks such as foursquare or Gowalla, it is now possible to explore a third generation of recommender systems, where knowledge about how the place had been used in the past (historical use) or is used at the moment of the inquiry (real-time use) by communities of users is the key element of the system. The main motivation behind the GALE project is to pioneer such third generation recommender systems which would make it possible for the rapidly growing population of "global" city users to access a level of information, that of the neighborhoods knowledge, which is inherently inaccessible to global repositories, and to do that in real time.