A measurement study of online internet video views through a large-scale, search engine

2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI:10.1109/CYBERC.2009.5342142

Yishuai Chen, Changjia Chen, Guo Dan

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引用次数: 3

Abstract

As the spread of broadband internet access, the online Internet video becomes popular in our daily life. The search engine is an important tool for users to access online video, resulting in considerable traffic on the video websites. In this work, we statistically analyze the video access log provided by a large scale video search engine, and validate that the aggregated views of online video from the search engine is diurnally regular. Furthermore, we find the probability of abrupt surge or disappearance of views is significantly high, having a percentage of 20% all videos. The results also show that 30% of them are spike that indicates that an accessing surge of views is followed by an immediate and abrupt falling. Such a result renders the big challenge how the website providers can satisfy the quality of service in providing their videos to users during the surging period. The online video access also indicates the social behaviors of the corresponding social group. These results are revealed by studying the querying string at the search engine. These results can be useful for the website developer to optimize the video system by allocating appropriate system resources according to the accessing habits of the users.

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通过大规模搜索引擎对在线互联网视频观看量的测量研究

随着宽带互联网接入的普及，网络视频在我们的日常生活中越来越受欢迎。搜索引擎是用户访问在线视频的重要工具，为视频网站带来了可观的流量。本文对某大型视频搜索引擎提供的视频访问日志进行了统计分析，验证了该搜索引擎对在线视频的聚合浏览量是每日规律的。此外，我们发现观看量突然激增或消失的概率非常高，占所有视频的20%。结果还显示，其中30%是峰值，这表明访问次数激增之后立即突然下降。这样的结果对网站提供商如何在激增时期为用户提供满意的视频服务质量提出了巨大的挑战。在线视频访问也反映了相应社会群体的社会行为。这些结果是通过在搜索引擎上研究查询字符串得到的。这些结果可以帮助网站开发人员根据用户的访问习惯分配适当的系统资源来优化视频系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery

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