期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2011
卷号：34
期号：02
出版社：IEEE Computer Society
摘要：Recommendation is the task of providing content that is likely to interest users and enrich their online expe-
rience. At Yahoo!, the variety of user-facing applications and the nature and volume of data raise multiple
recommendation opportunities and challenges. In this paper, we provide a brief description of several projects
within Yahoo! Labs, in the context of Web Search (Section 2), interpreting users’ clicks and browsing behavior
(Section 3), and on the Social Web (Section 4)
