Global context enhanced graph neural networks for session-based recommendation
Session-based recommendation (SBR) is a challenging task, which aims at recommending
items based on anonymous behavior sequences. Almost all the existing solutions for SBR …
items based on anonymous behavior sequences. Almost all the existing solutions for SBR …
Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations
In the field of sequential recommendation, deep learning--(DL) based methods have
received a lot of attention in the past few years and surpassed traditional models such as …
received a lot of attention in the past few years and surpassed traditional models such as …
Graph learning approaches to recommender systems: A review
Recent years have witnessed the fast development of the emerging topic of Graph Learning
based Recommender Systems (GLRS). GLRS mainly employ the advanced graph learning …
based Recommender Systems (GLRS). GLRS mainly employ the advanced graph learning …
Towards cognitive recommender systems
Intelligence is the ability to learn from experience and use domain experts' knowledge to
adapt to new situations. In this context, an intelligent Recommender System should be able …
adapt to new situations. In this context, an intelligent Recommender System should be able …
Intention nets: psychology-inspired user choice behavior modeling for next-basket prediction
Human behaviors are complex, which are often observed as a sequence of heterogeneous
actions. In this paper, we take user choices for shopping baskets as a typical case to study …
actions. In this paper, we take user choices for shopping baskets as a typical case to study …
Intention2basket: A neural intention-driven approach for dynamic next-basket planning
User purchase behaviours are complex and dynamic, which are usually observed as
multiple choice actions across a sequence of shopping baskets. Most of the existing next …
multiple choice actions across a sequence of shopping baskets. Most of the existing next …
[PDF][PDF] The Era of Intelligent Recommendation: Editorial on Intelligent Recommendation with Advanced AI and Learning.
After our announcement in early August 2019 for this special issue, we received 40
submissions, only 8 ones out of which are accepted to be included in this special issue. After …
submissions, only 8 ones out of which are accepted to be included in this special issue. After …
A survey on heterogeneous one-class collaborative filtering
Recommender systems play an important role in providing personalized services for users
in the context of information overload. Generally, users' feedback toward items often contain …
in the context of information overload. Generally, users' feedback toward items often contain …
Sentiment-guided sequential recommendation
L Zheng, N Guo, W Chen, J Yu, D Jiang - Proceedings of the 43rd …, 2020 - dl.acm.org
The existing sequential recommendation methods focus on modeling the temporal
relationships of user behaviors and are good at using additional item information to improve …
relationships of user behaviors and are good at using additional item information to improve …
Intention modeling from ordered and unordered facets for sequential recommendation
X Guo, C Shi, C Liu - Proceedings of The Web Conference 2020, 2020 - dl.acm.org
Recently, sequential recommendation has attracted substantial attention from researchers
due to its status as an essential service for e-commerce. Accurately understanding user …
due to its status as an essential service for e-commerce. Accurately understanding user …