2015
DOI: 10.1016/j.eswa.2014.12.043
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Extended topology based recommendation system for unidirectional social networks

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Cited by 14 publications
(9 citation statements)
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References 17 publications
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“…In (Yigit et al 2015) the authors present an extending topology based algorithm for recommending users in Twitter. The proposed algorithm classifies the users according to their friendship relations and constructs a class including user ids to recommend the target user.…”
Section: Collaborative Filteringmentioning
confidence: 99%
“…In (Yigit et al 2015) the authors present an extending topology based algorithm for recommending users in Twitter. The proposed algorithm classifies the users according to their friendship relations and constructs a class including user ids to recommend the target user.…”
Section: Collaborative Filteringmentioning
confidence: 99%
“…This mechanism works like a subscription of an information source. There are researches on recommendation systems that suggest which users the user should follow to get most interesting information for him or her [14][15][16].…”
Section: Introductionmentioning
confidence: 99%
“…Content based, demographic based, collaborative filtering are a few types of filtering 978-1-4673-6540-6/15/$31.00 ©20 15 IEEE algorithms. A continuous increment has been noticed in the implementation of recommender system in internet over the time that has facilitated its use in various areas like movie recommendation [6] [13], music recommendation [7], books [12], travel and tourism [19], e-commerce [II], B2B applications [21], social network [22], and web search [9] etc. To assess the relative worth of a recommender system various evaluation metrics have been proposed [14].…”
Section: Introductionmentioning
confidence: 99%