# Sequential Recommendation

67 papers with code • 1 benchmarks • 2 datasets

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## Libraries

Use these libraries to find Sequential Recommendation models and implementations
4 papers
13,212

# Self-Attentive Sequential Recommendation

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.

5

# BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

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.

5

# TiSASRec: Time Interval Aware Self-Attention for Sequential Recommendation

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.

4

# Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding

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'.

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# Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation

User modeling is an essential task for online rec- ommender systems.

2

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

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.

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

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.

2

# Hierarchical Gating Networks for Sequential Recommendation

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.

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# CosRec: 2D Convolutional Neural Networks for Sequential Recommendation

27 Aug 2019

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

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# SSE-PT: Sequential Recommendation Via Personalized Transformer

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.

2