News Recommendation

31 papers with code • 1 benchmarks • 1 datasets

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Use these libraries to find News Recommendation models and implementations
5 papers


Most implemented papers

RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

hwwang55/RippleNet 9 Mar 2018

To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance.

Fastformer: Additive Attention Can Be All You Need

wuch15/Fastformer 20 Aug 2021

In this way, Fastformer can achieve effective context modeling with linear complexity.

Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms

antonismand/Personalized-News-Recommendation 31 Mar 2010

\emph{Offline} evaluation of the effectiveness of new algorithms in these applications is critical for protecting online user experiences but very challenging due to their "partial-label" nature.

DKN: Deep Knowledge-Aware Network for News Recommendation

microsoft/recommenders 25 Jan 2018

To solve the above problems, in this paper, we propose a deep knowledge-aware network (DKN) that incorporates knowledge graph representation into news recommendation.

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

hwwang55/MKR 23 Jan 2019

Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems.

Neural News Recommendation with Attentive Multi-View Learning

microsoft/recommenders 12 Jul 2019

In the user encoder we learn the representations of users based on their browsed news and apply attention mechanism to select informative news for user representation learning.

News Session-Based Recommendations using Deep Neural Networks

gabrielspmoreira/chameleon_recsys 31 Jul 2018

This architecture is composed of two modules, the first responsible to learn news articles representations, based on their text and metadata, and the second module aimed to provide session-based recommendations using Recurrent Neural Networks.

Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks

gabrielspmoreira/chameleon_recsys 15 Apr 2019

The recommendation of news is often considered to be challenging, since the relevance of an article for a user can depend on a variety of factors, including the user's short-term reading interests, the reader's context, or the recency or popularity of an article.

A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems

PaddlePaddle/PaddleRec WWW 2015

We extend the model to jointly learn from features of items from different domains and user features by introducing a multi-view Deep Learning model.