Attentive multi-view learning model learns unified news representations from titles, bodies and categories and user representations from browsed news to improve recommendation performance.
From chatter to headlines: harnessing the real-time web for personalized news recommendation
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Neural News Recommendation with Attentive Multi-View Learning
Attentive multi-view learning model learns unified news representations from titles, bodies and categories and user representations from browsed news to improve recommendation performance.