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Interest-Aware Content Discovery in Peer-to-Peer Social Networks

Published:25 May 2018Publication History
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Abstract

With the increasing popularity and rapid development of Online Social Networks (OSNs), OSNs not only bring fundamental changes to information and communication technologies, but also make an extensive and profound impact on all aspects of our social life. Efficient content discovery is a fundamental challenge for large-scale distributed OSNs. However, the similarity between social networks and online social networks leads us to believe that the existing social theories are useful for improving the performance of social content discovery in online social networks. In this article, we propose an interest-aware social-like peer-to-peer (IASLP) model for social content discovery in OSNs by mimicking ten different social theories and strategies. In the IASLP network, network nodes with similar interests can meet, help each other, and co-operate autonomously to identify useful contents. The presented model has been evaluated and simulated in a dynamic environment with an evolving network. The experimental results show that the recall of IASLP is 20% higher than the existing method SESD while the overhead is 10% lower. The IASLP can generate higher flexibility and adaptability and achieve better performance than the existing methods.

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    • Published in

      cover image ACM Transactions on Internet Technology
      ACM Transactions on Internet Technology  Volume 18, Issue 3
      Special Issue on Artificial Intelligence for Secruity and Privacy and Regular Papers
      August 2018
      314 pages
      ISSN:1533-5399
      EISSN:1557-6051
      DOI:10.1145/3185332
      • Editor:
      • Munindar P. Singh
      Issue’s Table of Contents

      Copyright © 2018 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 25 May 2018
      • Accepted: 1 December 2017
      • Revised: 1 October 2017
      • Received: 1 June 2016
      Published in toit Volume 18, Issue 3

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