A survey on session-based recommender systems
Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …
consumption, services, and decision-making in the overloaded information era and digitized …
Star graph neural networks for session-based recommendation
Session-based recommendation is a challenging task. Without access to a user's historical
user-item interactions, the information available in an ongoing session may be very limited …
user-item interactions, the information available in an ongoing session may be very limited …
Graph and sequential neural networks in session-based recommendation: A survey
Recent years have witnessed the remarkable success of recommendation systems (RSs) in
alleviating the information overload problem. As a new paradigm of RSs, session-based …
alleviating the information overload problem. As a new paradigm of RSs, session-based …
Price does matter! modeling price and interest preferences in session-based recommendation
Session-based recommendation aims to predict items that an anonymous user would like to
purchase based on her short behavior sequence. The current approaches towards session …
purchase based on her short behavior sequence. The current approaches towards session …
Collaborative graph learning for session-based recommendation
Session-based recommendation (SBR), which mainly relies on a user's limited interactions
with items to generate recommendations, is a widely investigated task. Existing methods …
with items to generate recommendations, is a widely investigated task. Existing methods …
Enhancing hierarchy-aware graph networks with deep dual clustering for session-based recommendation
Session-based Recommendation aims at predicting the next interacted item based on short
anonymous behavior sessions. However, existing solutions neglect to model two inherent …
anonymous behavior sessions. However, existing solutions neglect to model two inherent …
AutoGSR: Neural architecture search for graph-based session recommendation
Session-based recommendation aims to predict next click action (eg, item) of anonymous
users based on a fixed number of previous actions. Recently, Graph Neural Networks …
users based on a fixed number of previous actions. Recently, Graph Neural Networks …
Exploiting explicit and implicit item relationships for session-based recommendation
The session-based recommendation aims to predict users' immediate next actions based on
their short-term behaviors reflected by past and ongoing sessions. Graph neural networks …
their short-term behaviors reflected by past and ongoing sessions. Graph neural networks …
Dynamic global structure enhanced multi-channel graph neural network for session-based recommendation
Session-based recommendation is a challenging task, which aims at making
recommendation for anonymous users based on in-session data, ie short-term interaction …
recommendation for anonymous users based on in-session data, ie short-term interaction …
[PDF][PDF] Learning Mutual Correlation in Multimodal Transformer for Speech Emotion Recognition.
Y Wang, G Shen, Y Xu, J Li, Z Zhao - Interspeech, 2021 - researchgate.net
Various studies have confirmed the necessity and benefits of leveraging multimodal features
for SER, and the latest research results show that the temporal information captured by the …
for SER, and the latest research results show that the temporal information captured by the …