基于情境感知技术的移动数据自动采集系统设计与实现
发布时间：2018-09-10 15:55
【摘要】：【目的】为移动环境下数据采集与分析提供一种基于情境感知技术(Context Awareness)的设计框架,以优化移动数据自动化采集过程。【应用背景】尽管基于移动端的情景感知数据采集较之传统网络环境下的人工与半自动方式有所发展,但利用移动端底层传感器直接获取实时用户信息,实现实时、动态、全面的数据采集与挖掘进而达到主动提供服务的目的,这方面的应用仍处于发展阶段。【方法】利用Android自带的众多传感器,设计了客户端自动采集、服务器主动接收的数据采集框架。在实证与评价方面,设计了一个通过动态情境感知推荐高层服务的实例。【结果】实证结果表明:该系统能够针对某一情境采集移动用户数据,为高层推荐服务提供良好支持。【局限】采集到的数据具有较大的冗余度,未进行多角度、全面、深度的情境推理,需要在以后的研究中针对用户数据进行深入分析。【结论】基于情境感知的移动数据自动采集系统能够进行移动数据的主动采集,并依据采集结果对个体或群体进行推送服务,对移动环境下用户行为研究与情境计算研究都起到较好的支撑作用。
[Abstract]:[objective] to provide a design framework for data acquisition and analysis in mobile environment based on situational awareness technology (Context Awareness). In order to optimize the automatic acquisition process of mobile data. [application background] although scenario sensing data acquisition based on mobile end has developed compared with manual and semi-automatic methods in traditional network environment, However, real-time user information can be directly obtained by using mobile end bottom sensor to realize real-time, dynamic and comprehensive data acquisition and mining to achieve the purpose of actively providing services. The application of this aspect is still in the developing stage. [methods] A data acquisition framework is designed based on Android sensors, which is automatically collected by the client and actively received by the server. In the aspect of demonstration and evaluation, an example is designed to recommend high-level services through dynamic situational awareness. [results] the empirical results show that the system can collect mobile user data for a given situation. To provide good support for high-level referral services. [limitations] the data collected have greater redundancy, without multi-angle, comprehensive, in-depth situational reasoning, It is necessary to analyze the user data deeply in the future research. [conclusion] the automatic mobile data acquisition system based on situational perception can collect mobile data actively and push service to individuals or groups according to the result of collection. It plays a good supporting role in the research of user behavior and situational computing in mobile environment.
【作者单位】： 华中师范大学信息管理学院;
【基金】：国家社会科学基金重大项目“基于多维度聚合的网络资源知识发现研究”(项目编号:13&ZD183) 国家自然科学青年基金项目“基于QSIM的图书馆移动用户群体行为模拟与学习兴趣引导研究”(项目编号:71503097)的研究成果之一
【分类号】：TP274.2
[Abstract]:[objective] to provide a design framework for data acquisition and analysis in mobile environment based on situational awareness technology (Context Awareness). In order to optimize the automatic acquisition process of mobile data. [application background] although scenario sensing data acquisition based on mobile end has developed compared with manual and semi-automatic methods in traditional network environment, However, real-time user information can be directly obtained by using mobile end bottom sensor to realize real-time, dynamic and comprehensive data acquisition and mining to achieve the purpose of actively providing services. The application of this aspect is still in the developing stage. [methods] A data acquisition framework is designed based on Android sensors, which is automatically collected by the client and actively received by the server. In the aspect of demonstration and evaluation, an example is designed to recommend high-level services through dynamic situational awareness. [results] the empirical results show that the system can collect mobile user data for a given situation. To provide good support for high-level referral services. [limitations] the data collected have greater redundancy, without multi-angle, comprehensive, in-depth situational reasoning, It is necessary to analyze the user data deeply in the future research. [conclusion] the automatic mobile data acquisition system based on situational perception can collect mobile data actively and push service to individuals or groups according to the result of collection. It plays a good supporting role in the research of user behavior and situational computing in mobile environment.
【作者单位】： 华中师范大学信息管理学院;
【基金】：国家社会科学基金重大项目“基于多维度聚合的网络资源知识发现研究”(项目编号:13&ZD183) 国家自然科学青年基金项目“基于QSIM的图书馆移动用户群体行为模拟与学习兴趣引导研究”(项目编号:71503097)的研究成果之一
【分类号】：TP274.2
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相关期刊论文 前7条
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本文编号：2234914
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