Context-aware news recommender in mobile hybrid P2P network

Kam Fung Yeung, Yanyan Yang, David Ndzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the emergence of pervasive environment, mobile recommender needs to make use of user in-time contextual information to provide personalized recommendation. In this paper, a proactive context-aware news recommender in mobile hybrid P2P network is designed and implemented. We develop a general Analytic Hierarchy Process (AHP) model through empirical studies. We discuss how the relative weight of each AHP criteria can be computed via user assignment and user history. We combine both Contend-based filtering and Collaborative filtering approach to predict user interest using Bayesian Network. The experiments show the system can recommend real time news stories that satisfy the user.

Original languageEnglish
Title of host publicationProceedings - 2nd International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages54-59
Number of pages6
ISBN (Print)9780769541587
DOIs
Publication statusPublished - 28 Jul 2010
Event2nd International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2010 - Liverpool, United Kingdom
Duration: 28 Jul 201030 Jul 2010

Conference

Conference2nd International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2010
Country/TerritoryUnited Kingdom
CityLiverpool
Period28/07/1030/07/10

Keywords

  • Analytic Hierarchy Process
  • Bayesian Network
  • collaborative filtering
  • content-based filtering
  • personalized Recommendation
  • proactively

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