Online Video Data Analytics

Benjamin Le, Jefferson Lai, Pierce Vollucci, Wenxuan Cai and Yaohui Ye

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2015-70
May 13, 2015

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-70.pdf

This capstone project report covers the research and development of Smart Anomaly Detection and Subscriber 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 and evaluate two algorithms used to detect anomalies in seasonal time series of service quality metrics, Autoregression and Seasonal Hybrid Extreme Student Deviate.

Advisor: George Necula


BibTeX citation:

@mastersthesis{Le:EECS-2015-70,
    Author = {Le, Benjamin and Lai, Jefferson and Vollucci, Pierce and Cai, Wenxuan and Ye, Yaohui},
    Editor = {Necula, George and Wroblewski, Don},
    Title = {Online Video Data Analytics},
    School = {EECS Department, University of California, Berkeley},
    Year = {2015},
    Month = {May},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-70.html},
    Number = {UCB/EECS-2015-70},
    Abstract = {This capstone project report covers the research and development of Smart Anomaly Detection and Subscriber 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 and evaluate two algorithms used to detect anomalies in seasonal time series of service quality metrics, Autoregression and Seasonal Hybrid Extreme Student Deviate.}
}

EndNote citation:

%0 Thesis
%A Le, Benjamin
%A Lai, Jefferson
%A Vollucci, Pierce
%A Cai, Wenxuan
%A Ye, Yaohui
%E Necula, George
%E Wroblewski, Don
%T Online Video Data Analytics
%I EECS Department, University of California, Berkeley
%D 2015
%8 May 13
%@ UCB/EECS-2015-70
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-70.html
%F Le:EECS-2015-70