What is recorded here?
Simplified graph collaborative filtering to normalized linear neighborhood embedding propagation and weighted combination across depths, omitting intermediate feature transforms and nonlinear activations.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Distinct from SGC's attributed-node linear classifier; here learned ID embeddings and user–item interaction graphs serve collaborative filtering. Source ablations do not prove nonlinear features useless in all recommender settings. Original template Conference17/placeholderDOI is not actual2017publication.
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People and systems
Xiangnan He; Kuan Deng; Xiang Wang; Yan Li; Yongdong Zhang; Meng Wang
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
LightGCN: linear embedding propagation for collaborative filtering
Simplified graph collaborative filtering to normalized linear neighborhood embedding propagation and weighted combination across depths, omitting intermediate feature transforms and nonlinear activations.
Scientific scope
Distinct from SGC's attributed-node linear classifier; here learned ID embeddings and user–item interaction graphs serve collaborative filtering. Source ablations do not prove nonlinear features useless in all recommender settings. Original template Conference17/placeholderDOI is not actual2017publication.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Xiangnan He; Kuan Deng; Xiang Wang; Yan Li; Yongdong Zhang; Meng Wang
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.