计算机科学 ›› 2016, Vol. 43 ›› Issue (7): 57-61.doi: 10.11896/j.issn.1002-137X.2016.07.009

• 2015年第二十四届全国多媒体学术会议 • 上一篇    下一篇

上下文信息对移动视频推送的影响分析

曾铖淋,王智,张瑾,林永君   

  1. 清华大学深圳研究生院计算机系 深圳518055,清华大学深圳研究生院计算机系 深圳518055,中国人民大学商学院 北京100872,清华大学深圳研究生院计算机系 深圳518055
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金:移动社交媒体服务的朵云部署理论与方法研究(61402247)资助

Analysis on Impact of Context on Mobile Video Push Notification

ZENG Cheng-lin, WANG Zhi, ZHANG Jin and LAM Ringo   

  • Online:2018-12-01 Published:2018-12-01

摘要: 在移动视频内容推送中,用户是否最终接受推送的视频内容不但取决于内容本身,还受用户所处的上下文(包括用户使用视频服务的时间、用户所在的位置,以及用户所使用接受视频内容的设备)的影响。上下文对用户接受移动视频内容的影响对移动视频推送具有重要意义。通过数据驱动的方法,利用大量移动用户在真实移动视频服务中接受视频推荐的记录(包括16天共4千万条移动视频访问日志),研究包括时间、位置、设备等上下文信息对用户最终接受移动视频内容的影响。基于实验数据给出的发现包括:(1)时间的周期性和峰值差异性;(2)位置的差异性和特殊区域的不同影响;(3)移动设备类型、移动操作系统的不同影响。这些研究结果将有助于优化移动视频内容的推送,提高用户的移动视频服务体验,例如,用户可以在偏好的上下文背景下获得更好的移动视频推送服务。

关键词: 上下文,移动视频,推送,测量

Abstract: In mobile video content push notification,the acceptance of pushed content is affected by not only the contents (e.g.whethere the user is interested in the contents),but also the contextual factors,including when and where the user receives the pushed contents,and which type of device the user uses to receive it.It is surprising that there is little effort devoted to studying the impact of context on mobile video push notification.This paper used a data-driven approach to study the impact of time,location and device on push acceptance.Insights include:(1)the impact of time is periodical and the peak of time varies;(2)the location is an important factor that determines whether users accept the pushed mobile video;(3)devices and types of mobile OS also affect the pushed mobilevideo.Based on these studies,mobile video push notification can be improved,so that users can get better mobile video push notification service in their preferred contexts.

Key words: Context,Mobile video,Push notification,Measure

[1] Kantor P B,Rokach L,Ricci F,et al.Recommender systemshandbook[M].Springer,2011
[2] Panniello U,Gorgoglione M.A contextual modeling approach to context-aware recommender systems[C]∥Proceedings of the 3rd Workshop on Context-Aware Recommender Systems.2011
[3] Adamopoulos P,Tuzhilin A.Estimating the value of multi-di-mensional data sets in context-based recommender systems[C]∥Reesys Posters 2014.2014
[4] Wang L C,Meng X W,Zhang Y J.Context-Aware Recommender Systems[J].Journal of Software,2012,3(1):1-20(in Chinese) 王立才,孟祥武,张玉洁.上下文感知推荐系统[J].软件学报,2012,23(1):1-20
[5] Hai B Z,Xie R Y.Bayesian Network-based Context-aware Re-commendation Algorithm[J].Computer Science,2014,41(17):275-278(in Chinese) 海本斋,解瑞云.基于贝叶斯网络的上下文推荐算法[J].计算机科学,2014,41(7):275-278
[6] Savage N S,Baranski M,Chavez NE,et al.I’am feeling loco:a location based context aware recommendation system[M]∥Advances in Location-Based Services,Lecture Notes in Geoinformation and Cartography.Berlin:Springer,2012:37-52
[7] Yuan Q,Cong G,Ma Z,et al.Time-aware point-of-interest re-commendation[C]∥Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2013:363-372
[8] Phelan O,McCarthy K,Smyth B.Using twitter to recommend real-time topical news[C]∥Proceedings of the Third ACM Conference on Recommender Systems.ACM,2009:385-388
[9] Son J W,Kim A,Park S B.A location-based news article recommendation with explicit localized semantic analysis[C]∥Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2013:293-302
[10] Zhou Y,Dai M H.News Recommendation Technology Combining Semantic Analysis with TF-IDF Method[J].Computer Science,2013,0(11A),267-269(in Chinese) 周由,戴牡红.语义分析与TF-IDF方法相结合的新闻推荐技术[J].计算机科学,2013,40(11A):267-269
[11] Yang X L,Qian C.News Recommender System Design Based on Subject Extraction and Memery Model[J].Computer & Digital Engineering,2012,0(6):47-50(in Chinese) 阳小兰,钱程.基于主题提取和记忆模型的新闻推荐系统设计[J].计算机与数字工程,2012,40(6):47-50
[12] Chen Z,Cao J,Song Y C,et al.Context-oriented web video tag recommendation[C]∥Proceedings of the 19th International Conference on World Wide Web.ACM,2010:1079-1080
[13] Li P,Yu X Y,Sun B Y.Video Recommendation Method Based on Group User Behavior Analysis[J].Journal of Electronics & Information Technology,2014,6(6):1485-1491(in Chinese) 李鹏,于晓洋,孙渤禹.基于用户群组行为分析的视频推荐方法研究[J].电子与信息学报,2014,36(6):1485-1491

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