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Improving One-class Recommendation with Multi-tasking on Various Preference Intensities
However, these efforts assume that all positive signals from implicit feedback reflect a fixed preference intensity, which is not realistic.
Learning Unsupervised Semantic Document Representation for Fine-grained Aspect-based Sentiment Analysis
Document representation is the core of many NLP tasks on machine understanding.
Revisiting Neighborhood-based Link Prediction for Collaborative Filtering
While there is a rich literature of such works using advanced models for learning user and item representations separately, item recommendation is essentially a link prediction problem between users and items.
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