Large-Scale Graph Mining and Learning for Information Retrieval

被引:0
|
作者
Gao, Bin [1 ]
Wang, Taifeng [1 ]
Liu, Tie-Yan [1 ]
机构
[1] Microsoft Res Asia, 5 Danling St, Beijing 100080, Peoples R China
关键词
Large-scale graph; graph ranking; Markov process; Map-Reduce;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For many information retrieval applications, we need to deal with the ranking problem on very large scale graphs. However, it is non-trivial to perform efficient and effective ranking on them. On one aspect, we need to design scalable algorithms. On another aspect, we also need to develop powerful computational infrastructure to support these algorithms. This tutorial aims at giving a timely introduction to the promising advances in the aforementioned aspects in recent years, and providing the audiences with a comprehensive view on the related literature.
引用
收藏
页码:1194 / 1195
页数:2
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