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

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)823-835
Number of pages13
JournalFuture Generation Computer Systems
Volume27
Issue number6
DOIs
Publication statusPublished - 2011 Jun 1

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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