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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.

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