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The recommendation systems task is to produce a list of recommendations for a user.

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Datasets

Greatest papers with code

Microsoft Recommenders: Tools to Accelerate Developing Recommender Systems

27 Aug 2020microsoft/recommenders

The purpose of this work is to highlight the content of the Microsoft Recommenders repository and show how it can be used to reduce the time involved in developing recommender systems.

RECOMMENDATION SYSTEMS

LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

6 Feb 2020microsoft/recommenders

We propose a new model named LightGCN, including only the most essential component in GCN -- neighborhood aggregation -- for collaborative filtering.

GRAPH CLASSIFICATION RECOMMENDATION SYSTEMS

A Simple Convolutional Generative Network for Next Item Recommendation

15 Aug 2018microsoft/recommenders

Convolutional Neural Networks (CNNs) have been recently introduced in the domain of session-based next item recommendation.

RECOMMENDATION SYSTEMS

xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems

14 Mar 2018microsoft/recommenders

On one hand, the xDeepFM is able to learn certain bounded-degree feature interactions explicitly; on the other hand, it can learn arbitrary low- and high-order feature interactions implicitly.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

DKN: Deep Knowledge-Aware Network for News Recommendation

25 Jan 2018microsoft/recommenders

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

CLICK-THROUGH RATE PREDICTION COMMON SENSE REASONING RECOMMENDATION SYSTEMS

Neural Collaborative Filtering

WWW 2017 microsoft/recommenders

When it comes to model the key factor in collaborative filtering -- the interaction between user and item features, they still resorted to matrix factorization and applied an inner product on the latent features of users and items.

RECOMMENDATION SYSTEMS INFORMATION RETRIEVAL

Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue

IJCNLP 2019 facebookresearch/ParlAI

These issues can be alleviated by treating recommendation as an interactive dialogue task instead, where an expert recommender can sequentially ask about someone's preferences, react to their requests, and recommend more appropriate items.

RECOMMENDATION SYSTEMS

FLEN: Leveraging Field for Scalable CTR Prediction

12 Nov 2019shenweichen/DeepCTR

By suitably exploiting field information, the field-wise bi-interaction pooling captures both inter-field and intra-field feature conjunctions with a small number of model parameters and an acceptable time complexity for industrial applications.

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS

Deep Session Interest Network for Click-Through Rate Prediction

16 May 2019shenweichen/DeepCTR

Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt, Deep Session Interest Network(DSIN)

CLICK-THROUGH RATE PREDICTION RECOMMENDATION SYSTEMS