位置相关的异构社交网络中行为关联与预测研究

项目名称： 位置相关的异构社交网络中行为关联与预测研究

项目编号： No.61472081

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 自动化技术、计算机技术

项目作者： 曹玖新

作者单位： 东南大学

项目金额： 83万元

中文摘要： 新一代位置相关的社交网络通过位置特征将虚拟社交空间和现实行为空间连接起来，融合了线上关系与线下行为，应用范围及重要性日益凸显。现有社交网络研究成果难以对其结构特征进行刻画、基本理论难以对其异构空间关联关系进行分析，相关应用急需理论和技术突破。本项目以现有社交网络研究成果为基础，进行以下四个方面的研究：分析异构空间中的社交关系、用户位置关系、位置时序关系的基本特征，采用形式化描述方法，构建统一的异构社交网络模型；基于异构空间拓扑和现实签到记录，设计高效算法，计算用户在不同社群上的概率分布；将社群关系投影到行为空间，对用户社交关系、签到行为及两者之间相互作用三个方面进行统计分析，获取用于行为预测的特征；基于社群发现和行为分析，构建行为时空模型对频繁模式行为进行预测，运用链路预测方法对新增模式行为进行预测。在此基础上，实现用户行为分析和预测原型系统，为用户行为预测和位置服务提供理论和技术支撑。

中文关键词： 社交网络；异构空间；社群发现；行为分析；位置预测

英文摘要： Location feature in the new generation location social network has built bridges between the virtual social space and the real behavior space. It could fuse the online relationship with the offline behavior. Over the last few years, this kind of social network becomes increasingly important with progressively wider range of application. However, existing research on social networks still has difficulty describing the structural characteristics of this type of network and the basic theory also cannot analyze its heterogeneous space correlation very well, so some breakthroughs in theory and technology are urgently needed to promote the development of related applications. Based on the existing research of social networks, this project carries out the following four aspects of research: Firstly, we analyze the basic features of user-user relation, user-location relation and spatial-temporal relation in heterogeneous space, and establish the general model on the heterogeneous social network using formal description methods. Secondly, based on the heterogeneous space topology and real checkin data, efficient algorithm is designed to perform calculation of user probability distribution in different communities. Thirdly, data in the behavior space is divided according to the communities, and statistical analysis is conducted on social relation, checkin behavior and their interreaction to obtain the features used in the prediction. Fourthly, based on the community discovery and behavior analysis, we build the behavior spatiotemporal model to predict the repeated behaviors and apply the link prediction method to predict the new behaviors. On the basis of these, the behavior analysis and prediction prototype system will be implemented, which provides theoretical and technical support for user behavior prediction and location based services.

英文关键词： Social Network;Heterogeneous Space;Community Discovery;Behavior Analysis;Location Prediction