Session-Based Recommendations

75 papers with code • 7 benchmarks • 3 datasets

Recommendation based on a sequence of events. e.g. next item prediction


Use these libraries to find Session-Based Recommendations models and implementations
3 papers
2 papers

Most implemented papers

Xception: Deep Learning with Depthwise Separable Convolutions

tensorflow/models CVPR 2017

We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution followed by a pointwise convolution).

Session-based Recommendations with Recurrent Neural Networks

microsoft/recommenders 21 Nov 2015

We apply recurrent neural networks (RNN) on a new domain, namely recommender systems.

Recurrent Neural Networks with Top-k Gains for Session-based Recommendations

hidasib/GRU4Rec ICLR 2018

RNNs have been shown to be excellent models for sequential data and in particular for data that is generated by users in an session-based manner.

Session-based Recommendation with Graph Neural Networks


To obtain accurate item embedding and take complex transitions of items into account, we propose a novel method, i. e. Session-based Recommendation with Graph Neural Networks, SR-GNN for brevity.

Neural Attentive Session-based Recommendation

lijingsdu/sessionRec_NARM 13 Nov 2017

Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later.

Evaluation of Session-based Recommendation Algorithms

rn5l/session-rec 26 Mar 2018

In many real-world applications, however, such long-term profiles often do not exist and recommendations therefore have to be made solely based on the observed behavior of a user during an ongoing session.

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.

Personalized Graph Neural Networks with Attention Mechanism for Session-Aware Recommendation


The other is Dot-Product Attention mechanism, which draws on the Transformer net to explicitly model the effect of historical sessions on the current session.

Session-aware Linear Item-Item Models for Session-based Recommendation

jin530/SLIST 30 Mar 2021

Session-based recommendation aims at predicting the next item given a sequence of previous items consumed in the session, e. g., on e-commerce or multimedia streaming services.

Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks

mquad/hgru4rec 13 Jun 2017

Session-based recommendations are highly relevant in many modern on-line services (e. g. e-commerce, video streaming) and recommendation settings.