.png){kind=icon}
返回
Recommender systems
.png){kind=icon}
OA
AI
DOI：10.1016/j.physrep.2012.02.006.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers. (c) 2012 Elsevier B.V. All rights reserved.
Keyword:
Recommender systems
Information filtering
Networks
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
P
IF:
29.5
论文数:
3.0K
被引数:
3.8W
机构
引用论文
Comparison of the effects of intravenous methylprednisolone pulse versus oral prednisolone therapies on the first attack of minimal‐change nephrotic syndrome in adults.png)
Nephrology
NephrologyIF0
PREAI
分享收藏
Circulating Aggregated Platelets, Number of Platelets per Aggregate and Platelet Size in Chronic Dialysis PatientsNephron
NephronIF0
PREAI
分享收藏
查看更多内容