CPRS: A cloud-based program recommendation system for digital TV platforms

Chin Feng Lai, Jui Hung Chang, Chia Cheng Hu, Yueh Min Huang, Han Chieh Chao

研究成果: Article同行評審

37 引文 斯高帕斯(Scopus)

摘要

Traditional electronic program guides (EPGs) cannot be used to find popular TV programs. A personalized digital video broadcasting-terrestrial (DVB-T) digital TV program recommendation system is ideal for providing TV program suggestions based on statistics results obtained from analyzing large-scale data. The frequency and duration of the programs that users have watched are collected and weighted by data mining techniques. A large dataset produces results that best represent a viewer's preferences of TV programs in a specific area. To process such a massive amount of viewer preference data, the bottleneck of scalability and computing power must be removed. In this paper, an architecture for a TV program recommendation system based on cloud computing and a map-reduce framework, the map-reduce version of k-means and the k-nearest neighbor (kNN) algorithm, is introduced and applied. The proposed architecture provides a scalable and powerful backend to support the demand of large-scale data processing for a program recommendation system.

原文English
頁(從 - 到)823-835
頁數13
期刊Future Generation Computer Systems
27
發行號6
DOIs
出版狀態Published - 2011 6月 1

All Science Journal Classification (ASJC) codes

  • 軟體
  • 硬體和架構
  • 電腦網路與通信

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