News recommender systems–Survey and roads ahead
More and more people read the news online, eg, by visiting the websites of their favorite
newspapers or by navigating the sites of news aggregators. However, the abundance of …
newspapers or by navigating the sites of news aggregators. However, the abundance of …
Personalized news recommendation: Methods and challenges
Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …
information and alleviate information overload. Although it has been extensively studied …
A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship
YM Li, CT Wu, CY Lai - Decision support systems, 2013 - Elsevier
Online business transactions and the success of e-commerce depend greatly on the
effective design of a product recommender mechanism. This study proposes a social …
effective design of a product recommender mechanism. This study proposes a social …
On the current state of deep learning for news recommendation
The exponential outbreak of news articles makes it troublesome for the readers to find,
select and read the most relevant ones and alleviate the resulting information and cognitive …
select and read the most relevant ones and alleviate the resulting information and cognitive …
Survey on learning-to-rank based recommendation algorithms
黄震华， 张佳雯， 田春岐， 孙圣力， 向阳 - Journal of Software, 2015 - jos.org.cn
排序学习技术尝试用机器学习的方法解决排序问题, 已被深入研究并广泛应用于不同的领域,
如信息检索, 文本挖掘, 个性化推荐, 生物医学等. 将排序学习融入推荐算法中 …
如信息检索, 文本挖掘, 个性化推荐, 生物医学等. 将排序学习融入推荐算法中 …
A systematic review of recommender system for e-portfolio domain
The aim of this study was to improve the state of the art recommendation techniques in thee-
Portfolio domain. A Systematic Review method is used inthis literature review, with the …
Portfolio domain. A Systematic Review method is used inthis literature review, with the …
An effective recommendation model based on deep representation learning
J Ni, Z Huang, J Cheng, S Gao - Information Sciences, 2021 - Elsevier
Recommender system has recently attracted a lot of attention in the information service
community. Currently, most recommendation models use deep neural networks to learn user …
community. Currently, most recommendation models use deep neural networks to learn user …
SE-stacking: Improving user purchase behavior prediction by information fusion and ensemble learning
Online shopping behavior has the characteristics of rich granularity dimension and data
sparsity and presents a challenging task in e-commerce. Previous studies on user behavior …
sparsity and presents a challenging task in e-commerce. Previous studies on user behavior …
[PDF][PDF] 基于排序学习的推荐算法研究综述
黄震华， 张佳雯， 田春岐， 孙圣力， 向阳 - 软件学报, 2015 - jos.org.cn
排序学习技术尝试用机器学习的方法解决排序问题, 已被深入研究并广泛应用于不同的领域,
如信息检索, 文本挖掘, 个性化推荐, 生物医学等. 将排序学习融入推荐算法中 …
如信息检索, 文本挖掘, 个性化推荐, 生物医学等. 将排序学习融入推荐算法中 …
Using concept lattice for personalized recommendation system design
A novel personalized recommendation system (PRS) based on concept lattice is proposed
and used to discover valuable information according to users' requirements and interests …
and used to discover valuable information according to users' requirements and interests …