Graph learning based recommender systems: A review
Recent years have witnessed the fast development of the emerging topic of Graph Learning
based Recommender Systems (GLRS). GLRS employ advanced graph learning …
based Recommender Systems (GLRS). GLRS employ advanced graph learning …
Computational technologies for fashion recommendation: A survey
Fashion recommendation is a key research field in computational fashion research and has
attracted considerable interest in the computer vision, multimedia, and information retrieval …
attracted considerable interest in the computer vision, multimedia, and information retrieval …
A deep graph neural network-based mechanism for social recommendations
Z Guo, H Wang - IEEE Transactions on Industrial Informatics, 2020 - ieeexplore.ieee.org
Nowadays, the issue of information overload is gradually gaining exposure in the Internet of
Things (IoT), calling for more research on recommender system in advance for industrial IoT …
Things (IoT), calling for more research on recommender system in advance for industrial IoT …
Fi-gnn: Modeling feature interactions via graph neural networks for ctr prediction
Click-through rate (CTR) prediction is an essential task in web applications such as online
advertising and recommender systems, whose features are usually in multi-field form. The …
advertising and recommender systems, whose features are usually in multi-field form. The …
Robust spammer detection using collaborative neural network in Internet-of-Things applications
Spamming is emerging as a key threat to the Internet of Things (IoT)-based social media
applications. It will pose serious security threats to the IoT cyberspace. To this end, artificial …
applications. It will pose serious security threats to the IoT cyberspace. To this end, artificial …
Hierarchical graph convolutional networks for semi-supervised node classification
Graph convolutional networks (GCNs) have been successfully applied in node classification
tasks of network mining. However, most of these models based on neighborhood …
tasks of network mining. However, most of these models based on neighborhood …
Hierarchical fashion graph network for personalized outfit recommendation
Fashion outfit recommendation has attracted increasing attentions from online shopping
services and fashion communities. Distinct from other scenarios (eg, social networking or …
services and fashion communities. Distinct from other scenarios (eg, social networking or …
Personalized fashion outfit generation with user coordination preference learning
This paper focuses on personalized outfit generation, aiming to generate compatible fashion
outfits catering to given users. Personalized recommendation by generating outfits of …
outfits catering to given users. Personalized recommendation by generating outfits of …
Personalized fashion compatibility modeling via metapath-guided heterogeneous graph learning
Fashion Compatibility Modeling (FCM) is a new yet challenging task, which aims to
automatically access the matching degree among a set of complementary items. Most of …
automatically access the matching degree among a set of complementary items. Most of …
Diffusion models for generative outfit recommendation
Outfit Recommendation (OR) in the fashion domain has evolved through two stages: Pre-
defined Outfit Recommendation and Personalized Outfit Composition. However, both stages …
defined Outfit Recommendation and Personalized Outfit Composition. However, both stages …