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Movie Recommendation

Evaluates the ability of language models to propose relevant movie recommendations with collaborative filtering data.

Source: BIG-bench

Papers

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Showing 101–113 of 113 papers

TitleStatusHype
A case study of Empirical Bayes in User-Movie Recommendation system—0
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation—0
Could you guess an interesting movie from the posters?: An evaluation of vision-based features on movie poster database—0
Greed is Good: Near-Optimal Submodular Maximization via Greedy Optimization—0
Fast Distributed Submodular Cover: Public-Private Data Summarization—0
Online Categorical Subspace Learning for Sketching Big Data with Misses—0
Collaborative Filtering with Recurrent Neural NetworksCode0
Exponential Family Embeddings—0
A Survey of Point-of-interest Recommendation in Location-based Social Networks—0
Collaborative filtering via sparse Markov random fields—0
Using Shortlists to Support Decision Making and Improve Recommender System Performance—0
Learning From Missing Data Using Selection Bias in Movie Recommendation—0
Provable Inductive Matrix Completion—0
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