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24 June 2024
 
  » arxiv » 2302.00412

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KNNs of Semantic Encodings for Rating Prediction
Léo Laugier ; Thomas Bonald ; Lucas Dixon ; Raghuram Vadapalli ;
Date 1 Feb 2023
AbstractThis paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user’s preferences as a graph of textual snippets from review text, where the edges are defined by semantic similarity. This textual, memory-based approach to rating prediction enables review-based explanations for recommendations. The method is evaluated quantitatively, highlighting that leveraging text in this way outperforms both strong memory-based and model-based collaborative filtering baselines.
Source arXiv, 2302.00412
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