张恒才, 陆锋, 陈洁. 移动对象时空轨迹及社交关系一体化数据模型[J]. 武汉大学学报 ( 信息科学版), 2014, 39(6): 711-718. DOI: 10.13203/j.whugis20140125
引用本文: 张恒才, 陆锋, 陈洁. 移动对象时空轨迹及社交关系一体化数据模型[J]. 武汉大学学报 ( 信息科学版), 2014, 39(6): 711-718. DOI: 10.13203/j.whugis20140125
ZHANG Hengcai, LU Feng, CHEN Jie. An Integrated Data Model for Spatial-Temporal Trajectories and theSocial Relationships of Moving Objects[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 711-718. DOI: 10.13203/j.whugis20140125
Citation: ZHANG Hengcai, LU Feng, CHEN Jie. An Integrated Data Model for Spatial-Temporal Trajectories and theSocial Relationships of Moving Objects[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 711-718. DOI: 10.13203/j.whugis20140125

移动对象时空轨迹及社交关系一体化数据模型

An Integrated Data Model for Spatial-Temporal Trajectories and theSocial Relationships of Moving Objects

  • 摘要: 目的 泛地理信息时代来临及SoLoMo互联网模式盛行,如何高效管理移动对象位置数据、社交关系数据及地理空间数据成为GIS与移动对象数据库研究领域一项全新的技术挑战。首先基于图模型提出了移动对象时空轨迹及社交关系的一体化数据模型GSM,实现了移动对象所在地理空间、移动对象位置与轨迹、移动对象之间社交关系的时空一体化表达,并定义了该模型的四种基础操作算子;然后基于图数据库系统Neo4J实现了GSM模型;最后利用真实的Brightkite、Gowalla位置社交网络数据验证了GSM模型的有效性。所提出的GSM模型能够有效避免关系数据库中表连接造成的移动对象管理与查询效率低下的问题,具有良好的执行效率及稳定性,可为基于位置的社交网络应用提供核心技术支持。

     

    Abstract: Objective In the pan geographic information age,with the development of the SoLoMo(social,localand mobile)modes in the mobile internet industry,how to effectively manage massive location-baseddata,social network and geospatial data has become a major challenge in the moving object databasesfield of research.In this paper,a spatial-temporal integrated data model for moving object trajectoriesand social relationships,called the Geo-Social-Moving(GSM)model,is proposed to manage bothmoving object geographical locations,trajectories and social relationships in an integrated framework.We define a series of common operations including interception,extension,projection and multi-di-mensional projection.Then,the GSM model is implemented based on a graph database system.Weconducted detailed experiments with two free location-based social network datasets from Brightkiteand Gowalla to verified the effectiveness of the GSM model.Results show that the proposed GSMmodel can avoid query inefficiency caused by relational database table joins with the efficiency and sta-bility to provide support for location-based social network applications.

     

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