A Brief History of Recommender Systems
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Abstract (arXiv)
Soon after the invention of the Internet, the recommender system emerged and related technologies have been extensively studied and applied by both academia and industry. Currently, recommender system has become one of the most successful web applications, serving billions of people in each day through recommending different kinds of contents, including news feeds, videos, e-commerce products, music, movies, books, games, friends, jobs etc. These successful stories have proved that recommender system can transfer big data to high values. This article briefly reviews the history of web recommender systems, mainly from two aspects: (1) recommendation models, (2) architectures of typical recommender systems. We hope the brief review can help us to know the dots about the progress of web recommender systems, and the dots will somehow connect in the future, which inspires us to build more advanced recommendation services for changing the world better.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Sep 2022.
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Citing papers per year: 2023: 2; 2024: 0; 2025: 1; 2026: 1.
4 papers.
- 2026A Practical Algorithm for Feature-Rich, Non-Stationary Bandit Problems17 Mar 2026
- 2025Trends in AI Supercomputers22 Apr 2025
- 2023Ten Challenges in Industrial Recommender Systems7 Oct 2023
- 2023Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?16 Aug 2023