Social Recommendation Algorithm Dynamically Adaptable to User Profiling for SNS

Weimin Li, Yikai Ni, Minye Wu, Zhengbo Ye, Qun Jin

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

2 Citations (Scopus)

Abstract

With the development of social network services, the user relation spectrum of the social network has exceeded our imagination. Hence, personalized recommendation algorithms are adopted in many social networking sites to help users find their potential friends and related information more quickly and conveniently. In this paper, we discuss the weaknesses of current algorithms, and propose a user profile integrated dynamic social recommendation algorithm in order to overcome those limitations. Finally, through the experiment on Weibo dataset, it can conclude that the proposed algorithm outperforms traditional approaches in terms of accuracy and stability.

Original languageEnglish
Title of host publicationProceedings - 2014 2nd International Conference on Advanced Cloud and Big Data, CBD 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages261-266
Number of pages6
ISBN (Electronic)9781479980857
DOIs
Publication statusPublished - 2015 Aug 3
Event2nd International Conference on Advanced Cloud and Big Data, CBD 2014 - Huangshan, Anhui, China
Duration: 2014 Nov 202014 Nov 22

Publication series

NameProceedings - 2014 2nd International Conference on Advanced Cloud and Big Data, CBD 2014

Other

Other2nd International Conference on Advanced Cloud and Big Data, CBD 2014
Country/TerritoryChina
CityHuangshan, Anhui
Period14/11/2014/11/22

Keywords

  • Collaborative filtering
  • Dynamic recommendation
  • Profile matching
  • Social network

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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