Movie Recommendation

14 papers with code • 2 benchmarks • 2 datasets

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

Source: BIG-bench

Most implemented papers

Collaborative Filtering with Recurrent Neural Networks

rdevooght/sequence-based-recommendations 26 Aug 2016

We show that collaborative filtering can be viewed as a sequence prediction problem, and that given this interpretation, recurrent neural networks offer very competitive approach.

A Hybrid Variational Autoencoder for Collaborative Filtering

kilolgupta/Variational-Autoencoders-Collaborative-Filtering 14 Jul 2018

Our approach combines movie embeddings (learned from a sibling VAE network) with user ratings from the Movielens 20M dataset and applies it to the task of movie recommendation.

Movie Recommendation System using Sentiment Analysis from Microblogging Data

3ZadeSSG/ContentBased-Movie-Recommendation-using-Sentiment-Analysis 27 Nov 2018

Traditional approaches in recommendation systems include collaborative filtering and content-based filtering.

MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems

VisaoComputacional/mira 25 Feb 2019

The present project is inspired by the LIDA model to apply it to the process of movie recommendation, the model called MIRA (Movie Intelligent Recommender Agent) presented percentages of precision similar to a traditional model when submitted to the same assay conditions.

No-Regret Learning in Unknown Games with Correlated Payoffs

sessap/noregretgames NeurIPS 2019

We consider the problem of learning to play a repeated multi-agent game with an unknown reward function.

Streaming Submodular Maximization under a $k$-Set System Constraint

ehsankazemi/streamingkextendible 9 Feb 2020

In this paper, we propose a novel framework that converts streaming algorithms for monotone submodular maximization into streaming algorithms for non-monotone submodular maximization.

The Adapter-Bot: All-In-One Controllable Conversational Model

HLTCHKUST/adapterbot 28 Aug 2020

The dialogue skills can be triggered automatically via a dialogue manager, or manually, thus allowing high-level control of the generated responses.

INSPIRED: Toward Sociable Recommendation Dialog Systems

sweetpeach/Inspired EMNLP 2020

To better understand how humans make recommendations in communication, we design an annotation scheme related to recommendation strategies based on social science theories and annotate these dialogs.

Fairness in Streaming Submodular Maximization: Algorithms and Hardness

google-research/google-research NeurIPS 2020

Submodular maximization has become established as the method of choice for the task of selecting representative and diverse summaries of data.

Bias in Knowledge Graphs -- an Empirical Study with Movie Recommendation and Different Language Editions of DBpedia

voitijaner/Movie-RSs-Master-Thesis-Submission-Voit 3 May 2021

Public knowledge graphs such as DBpedia and Wikidata have been recognized as interesting sources of background knowledge to build content-based recommender systems.