依托大数据平台,我省于2017年完成OTT(Over The Top)定位算法和指纹库定位算法大数据平台部署、MDT(Minimization of Drive-Test)数据采集处理,从而实现全量MRO(Measurement Report Original)、S1mme、S1uhttp、Mw、Sv等接口信令数据的...依托大数据平台,我省于2017年完成OTT(Over The Top)定位算法和指纹库定位算法大数据平台部署、MDT(Minimization of Drive-Test)数据采集处理,从而实现全量MRO(Measurement Report Original)、S1mme、S1uhttp、Mw、Sv等接口信令数据的经纬度关联回填,定位分析能力由基站/小区拓展到局部区域或具体楼宇。为了深挖定位信令数据价值,提升定位信令数据网络线条应用能力,我省建立基于定位信令大数据的网络线条分析应用体系。通过体系建设及支撑手段开发应用,有效提升网络优化工作效率,并带动网络优化工作向自动化、智能化的变革,更为定位数据拓展挖掘奠定了丰富的工作经验。展开更多
User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube h...User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the users' watching and sharing activities.The substantial benefit is to further augment its service and monetize more videos,which is crucial to both YouTube and its partners,as well as to other providers of relevant services.In this paper,our main contribution is to analyze the massive amounts of video data from a YouTube partner's view.We make effective use of Insight,a new analytics service of YouTube that offers simple data analysis for partners.To provide the practical guidance from the raw Insight data,we enable more complex investigations for the inherent features that affect the popularity of the videos.Our findings facilitate YouTube partners to re-design current video publishing strategies,having more opportunities to attract more views.展开更多
文摘依托大数据平台,我省于2017年完成OTT(Over The Top)定位算法和指纹库定位算法大数据平台部署、MDT(Minimization of Drive-Test)数据采集处理,从而实现全量MRO(Measurement Report Original)、S1mme、S1uhttp、Mw、Sv等接口信令数据的经纬度关联回填,定位分析能力由基站/小区拓展到局部区域或具体楼宇。为了深挖定位信令数据价值,提升定位信令数据网络线条应用能力,我省建立基于定位信令大数据的网络线条分析应用体系。通过体系建设及支撑手段开发应用,有效提升网络优化工作效率,并带动网络优化工作向自动化、智能化的变革,更为定位数据拓展挖掘奠定了丰富的工作经验。
文摘User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the users' watching and sharing activities.The substantial benefit is to further augment its service and monetize more videos,which is crucial to both YouTube and its partners,as well as to other providers of relevant services.In this paper,our main contribution is to analyze the massive amounts of video data from a YouTube partner's view.We make effective use of Insight,a new analytics service of YouTube that offers simple data analysis for partners.To provide the practical guidance from the raw Insight data,we enable more complex investigations for the inherent features that affect the popularity of the videos.Our findings facilitate YouTube partners to re-design current video publishing strategies,having more opportunities to attract more views.
