A review of safe reinforcement learning: Methods, theory and applications
Reinforcement learning (RL) has achieved tremendous success in many complex decision
making tasks. When it comes to deploying RL in the real world, safety concerns are usually …
making tasks. When it comes to deploying RL in the real world, safety concerns are usually …
Artificial intelligence in E-Commerce: a bibliometric study and literature review
This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …
guidelines on how information systems (IS) research could contribute to this research …
[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; …
[PDF][PDF] 个性化推荐系统的研究进展
刘建国， 周涛， 汪秉宏 - 自然科学进展, 2009 - nsfc.gov.cn
摘要互联网技术的迅猛发展把我们带进了信息爆炸的时代. 海量信息的同时呈现,
一方面使用户很难从中发现自己感兴趣的部分, 另一方面也使得大量少人问津的信息成为网络中 …
一方面使用户很难从中发现自己感兴趣的部分, 另一方面也使得大量少人问津的信息成为网络中 …
Reinforcement learning based recommender systems: A survey
Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …
help us find our favorite items to purchase, our friends on social networks, and our favorite …
Self-supervised hypergraph convolutional networks for session-based recommendation
Session-based recommendation (SBR) focuses on next-item prediction at a certain time
point. As user profiles are generally not available in this scenario, capturing the user intent …
point. As user profiles are generally not available in this scenario, capturing the user intent …
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 …
Artificial intelligence in recommender systems
Recommender systems provide personalized service support to users by learning their
previous behaviors and predicting their current preferences for particular products. Artificial …
previous behaviors and predicting their current preferences for particular products. Artificial …
BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer
Modeling users' dynamic preferences from their historical behaviors is challenging and
crucial for recommendation systems. Previous methods employ sequential neural networks …
crucial for recommendation systems. Previous methods employ sequential neural networks …