Can you trust the user?: Collaborative trust estimation model for recommendations

Minami, Daichi; Ushiama, Taketoshi

doi:10.1109/icdim.2017.8244681

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2022

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“…There has also been significant advancement in recommender system research in recent years, including enhancements based on collaborative filtering algorithms [10][11][12][13]. The majority of these algorithms are enhancements to similarity calculations to choose individuals who are as similar as feasible.…”

Section: Related Workmentioning

confidence: 99%

Retracted: Collaborative learning‐assisted recommendation of social trust over Web of Things

Shrivastava

Saravanan²,

Rizwan

et al. 2022

IET Communications

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The above article from IET Communications, published online on 24 November 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Interim Editor‐in‐Chief, Jian Ren, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.

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Section: Related Workmentioning

confidence: 99%