ESLI: Enhancing slope one recommendation through local information embedding.

Slope one is a popular recommendation algorithm due to its simplicity and high efficiency for sparse data. However, it often suffers from under-fitting since the global information of all relevant users/items are considered. In this paper, we propose a new scheme called enhanced slope one recommenda...

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Bibliographic Details
Main Authors: Heng-Ru Zhang, Yuan-Yuan Ma, Xin-Chao Yu, Fan Min
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0222702

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