Blockchain-empowered federated learning: Challenges, solutions, and future directions

J Zhu, J Cao, D Saxena, S Jiang, H Ferradi - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …

Artificial intelligence in E-Commerce: a bibliometric study and literature review

RE Bawack, SF Wamba, KDA Carillo, S Akter - Electronic markets, 2022 - Springer
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 …

Uncovering chatgpt's capabilities in recommender systems

S Dai, N Shao, H Zhao, W Yu, Z Si, C Xu… - Proceedings of the 17th …, 2023 - dl.acm.org
The debut of ChatGPT has recently attracted significant attention from the natural language
processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT …

Economic complexity theory and applications

CA Hidalgo - Nature Reviews Physics, 2021 - nature.com
Economic complexity methods have become popular tools in economic geography,
international development and innovation studies. Here, I review economic complexity …

Evaluating recommender systems: survey and framework

E Zangerle, C Bauer - ACM Computing Surveys, 2022 - dl.acm.org
The comprehensive evaluation of the performance of a recommender system is a complex
endeavor: many facets need to be considered in configuring an adequate and effective …

Reinforcement learning based recommender systems: A survey

MM Afsar, T Crump, B Far - ACM Computing Surveys, 2022 - dl.acm.org
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 …

[PDF][PDF] 个性化推荐系统综述

王国霞, 刘贺平 - 计算机工程与应用, 2012 - 0xsky.com
信息超载是目前网络用户面临的一个严重问题, 个性化推荐系统是解决该问题的一个有力工具,
并受到了众多的关注和研究. 给出推荐系统的定义, 同时阐述了推荐系统的几项关键技术 …

Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems

R Wang, R Shivanna, D Cheng, S Jain, D Lin… - Proceedings of the web …, 2021 - dl.acm.org
Learning effective feature crosses is the key behind building recommender systems.
However, the sparse and large feature space requires exhaustive search to identify effective …

Conversational information seeking

H Zamani, JR Trippas, J Dalton… - … and Trends® in …, 2023 - nowpublishers.com
Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

Recommendation systems: Algorithms, challenges, metrics, and business opportunities

Z Fayyaz, M Ebrahimian, D Nawara, A Ibrahim… - applied sciences, 2020 - mdpi.com
Recommender systems are widely used to provide users with recommendations based on
their preferences. With the ever-growing volume of information online, recommender …