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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2019-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0222702 |