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在线视频数据分析

Online Video Data Analytics

作者:Jefferson Lai;Benjamin Le;Pierce Vollucci;Wenxuan Cai;Yaohui Ye;George Necula, Ed.;Don Wroblewski, Ed. 作者单位:Electrical Engineering and Computer Sciences University of California at Berkeley 加工时间:2015-07-05 信息来源:EECS 索取原文[71 页]
关键词:网络视频;数据分析;机器学习模型
摘 要:Analysis in the domain of Online Video Data Analytics. In the co-written portions of this document, we discuss the projected commercialization success of our products by analyzing worldwide trends in online video, presenting a competitive business strategy, and describing several approaches towards the management of our intellectual property. In the individually written portion of this document, we discuss our implementation of two machine learning models, k Nearest Neighbors and Random Forest, and evaluate them as a means of identifying subscription churners, the primary goal of Subscriber Analysis. In particular, we show that the performances achieved by these models using our initial, restricted feature set are promising and warrant future exploration of these models. 
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