Sequential Recommendation

67 papers with code • 1 benchmarks • 2 datasets

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Use these libraries to find Sequential Recommendation models and implementations
4 papers

Most implemented papers

Self-Attentive Sequential Recommendation

microsoft/recommenders 20 Aug 2018

Sequential dynamics are a key feature of many modern recommender systems, which seek to capture the `context' of users' activities on the basis of actions they have performed recently.

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

FeiSun/BERT4Rec 14 Apr 2019

To address this problem, we train the bidirectional model using the Cloze task, predicting the masked items in the sequence by jointly conditioning on their left and right context.

TiSASRec: Time Interval Aware Self-Attention for Sequential Recommendation

PaddlePaddle/PaddleRec 1 Jan 2020

Sequential recommender systems seek to exploit the order of users' interactions, in order to predict their next action based on the context of what they have done recently.

Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding

microsoft/recommenders 19 Sep 2018

Top-$N$ sequential recommendation models each user as a sequence of items interacted in the past and aims to predict top-$N$ ranked items that a user will likely interact in a `near future'.

Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation

XiaoZHOUCAM/TEMN 19 May 2019

Point-of-Interest (POI) recommender systems play a vital role in people's lives by recommending unexplored POIs to users and have drawn extensive attention from both academia and industry.

DeepRec: An Open-source Toolkit for Deep Learning based Recommendation

cheungdaven/DeepRec 25 May 2019

In this toolkit, we have implemented a number of deep learning based recommendation algorithms using Python and the widely used deep learning package - Tensorflow.

Hierarchical Gating Networks for Sequential Recommendation

allenjack/HGN 21 Jun 2019

However, with the tremendous increase of users and items, sequential recommender systems still face several challenging problems: (1) the hardness of modeling the long-term user interests from sparse implicit feedback; (2) the difficulty of capturing the short-term user interests given several items the user just accessed.

CosRec: 2D Convolutional Neural Networks for Sequential Recommendation

zzxslp/CosRec 27 Aug 2019

Sequential patterns play an important role in building modern recommender systems.

SSE-PT: Sequential Recommendation Via Personalized Transformer

SSE-PT/SSE-PT 25 Sep 2019

Recent advances in deep learning, especially the discovery of various attention mechanisms and newer architectures in addition to widely used RNN and CNN in natural language processing, have allowed for better use of the temporal ordering of items that each user has engaged with.