A review of content-based and context-based recommendation systems
In our work, we have presented two widely used recommendation systems. We have
presented a context-aware recommender system to filter the items associated with user's …
presented a context-aware recommender system to filter the items associated with user's …
A comprehensive survey of neighborhood-based recommendation methods
C Desrosiers, G Karypis - Recommender systems handbook, 2010 - Springer
Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …
[PDF][PDF] 互联网推荐系统比较研究
许海玲， 吴潇， 李晓东， 阎保平[1 - 软件学报, 2009 - jos.org.cn
全面地总结推荐系统的研究现状, 旨在介绍网络推荐的算法思想, 帮助读者了解这个研究领域.
首先阐述了推荐系统研究的工业需求, 主要研究机构和成果发表的期刊会议; …
首先阐述了推荐系统研究的工业需求, 主要研究机构和成果发表的期刊会议; …
Unmasking Clever Hans predictors and assessing what machines really learn
Current learning machines have successfully solved hard application problems, reaching
high accuracy and displaying seemingly intelligent behavior. Here we apply recent …
high accuracy and displaying seemingly intelligent behavior. Here we apply recent …
Cayleynets: Graph convolutional neural networks with complex rational spectral filters
The rise of graph-structured data such as social networks, regulatory networks, citation
graphs, and functional brain networks, in combination with resounding success of deep …
graphs, and functional brain networks, in combination with resounding success of deep …
Geometric matrix completion with recurrent multi-graph neural networks
Matrix completion models are among the most common formulations of recommender
systems. Recent works have showed a boost of performance of these techniques when …
systems. Recent works have showed a boost of performance of these techniques when …
Inductive matrix completion based on graph neural networks
We propose an inductive matrix completion model without using side information. By
factorizing the (rating) matrix into the product of low-dimensional latent embeddings of rows …
factorizing the (rating) matrix into the product of low-dimensional latent embeddings of rows …
How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
Recommendation systems are ubiquitous and impact many domains; they have the potential
to influence product consumption, individuals' perceptions of the world, and life-altering …
to influence product consumption, individuals' perceptions of the world, and life-altering …
Collaborative filtering recommender systems
Recommender systems are an important part of the information and e-commerce ecosystem.
They represent a powerful method for enabling users to filter through large information and …
They represent a powerful method for enabling users to filter through large information and …