论文标题

推荐系统的简短历史

A Brief History of Recommender Systems

论文作者

Dong, Zhenhua, Wang, Zhe, Xu, Jun, Tang, Ruiming, Wen, Jirong

论文摘要

互联网发明后不久,学术界和工业都广泛研究和应用了相关技术。目前,推荐系统已成为最成功的Web应用程序之一,每天通过推荐各种内容,包括新闻提要,视频,电子商务产品,音乐,电影,书籍,书籍,游戏,朋友,工作,工作。这些成功的故事已经证明,推荐系统可以将大数据传输到高价值。本文简要回顾了Web推荐系统的历史,主要来自两个方面:(1)建议模型,(2)典型推荐系统的体系结构。我们希望简短的评论能够帮助我们了解有关Web推荐系统进度的点,并且这些点将来会以某种方式连接,这激发了我们建立更高级的推荐服务,以更好地改变世界。

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.

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