随着移动互联网的发展和智能移动设备的普及，基于位置的服务和社交网络得到了广泛应用。近几年基于位置的社交网络得到了工业界和学术界的广泛关注。针对国内外的研究现状和发展趋势，本项目研究基于位置的社交网络的关键技术问题，以高质量获取社交网络用户的位置信息为切入点，设计基于位置的影响力分析模型，提出位置和结构感知的检索与推荐算法，创建一套完整的基于位置的社交网络数据处理的理论、方法和技术体系。项目具体研究内容包括：(1) 社交网络用户的位置信息获取：根据用户发表的内容、用户之间的关系以及多个社交网络用户的关联信息来挖掘用户的位置信息；(2) 面向多维度信息的用户影响力分析：研究面向多维度信息（例如用户位置、讨论话题、多社交网络等）的社交网络用户影响力分析模型；(3) 位置和结构感知的检索和推荐：研究利用用户位置信息和用户之间关系(结构)来为基于位置的社交网络用户提供高质量的检索和个性化推荐服务。

With the development and popularity of mobile networks and smart mobile devices, location-based services and social networks have been widely deployed. Location-based social networks recently attracted signifciant attention from the industry and academic communities.Based on the domestic and international research trends, this probject studies the key challenges and theory of location-based social networks. This project foucses on extracting high-quality locations of social network users, trying to make major breakthroughs in location-based influence analysis, and designing location and structure-aware search and recommendation algorithms. The project aims at developing a complete set of location-based social networks data processing theory, method and system. In summary, this project studies the following problems: (1) Location extraction for social-network users: extrating users'location information by mining user-published content, the relationship between users, and user corelations from different social networks. (2) Multi-dimensional influence analysis: devising multi-dimensional user influence analysis model by considering multi-dimensional information (such as user locations, discussion topics, etc.) .(3)Location and structure aware search and recommendation: integrating user locations and user structures to provide search and recommendation services and dveloping integration algorithms to support effective location and structure aware search and recommendation in location-based social networks.