图 书 馆
机器学习排名系统的提前退出优化Early Exit Optimizations for Additive Machine Learned Ranking Systems |
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| 课程网址: | http://videolectures.net/wsdm2010_cambazoglu_eeo/ |
| 主讲教师: | Berkant Barla Cambazoglu |
| 开课单位: | 雅虎公司 |
| 开课时间: | 2010-09-10 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Some commercial web search engines rely on sophisticated machine learning systems for ranking web documents. Due to very large collection sizes and tight constraints on query response times, online efficiency of these learning systems forms a bottleneck. An important problem in such systems is to speedup the ranking process without sacrificing much from the quality of results. In this paper, we propose optimization strategies that allow short-circuiting score computations in additive learning systems. The strategies are evaluated over a state-of-the-art machine learning system and a large, real-life query log, obtained from Yahoo!. By the proposed strategies, we are able to speedup the score computations by more than four times with almost no loss in result quality. |
| 关 键 词: | 商业网络; 搜索引擎; 机器学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-01-13：chenxin |
| 阅读次数: | 33 |