A Real-Time Data Filter for Interactive-TV Rating System

• Published in: Applied Mechanics and Materials Vol. 764-765; no. Modern Design Technologies and Experiment for Advanced Manufacture and Industry; pp. 792 - 795
• Main Authors: Wang, Hao Cheng, Chou, Shih Chun, Chen, Sheng Chang, Chen, Yung Lun, Wang, Rong Sheng, Lu, Yung Feng
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 28.05.2015
• Subjects: Algorithms; Filtering; Monitoring; Platforms; Ratings; Real time; Set top boxes; Trends; Viewing; Data Cleansing; Real-Time System; NoSQL; TV Ratings
• ISBN: 9783038354604; 3038354600
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.764-765.792

The set-top box (STB) connected to TVs are used to gather viewing data, which then is transmitted to a backend platform. It is very hard to analyze the viewing behavior since the viewing data are very huge and contain noise. This paper presents a real-time interactive-TV rating system for monitoring the trend of user viewing behavior. The system collects viewing behavior data from CATV system vendors, analyzes the data, and then provides real-time analysis diagrams. The authors also proposed two phases filtering algorithm that can efficiently check and filter the invalid viewing behavior according to the effective data filter rules. The algorithm can daily filter 27 million viewing behavior data and generate 7.6 million effective data. It can reduce the need of storage space and increase the analysis speed. In this works, we develop a real-time interactive-TV rating system for monitoring the trend of user viewing behavior and provide the real-time ratings for the last three minutes watched.