Crowd-sourcing Web Knowledge for Metadata Extraction

被引：0
|
作者：
Wu, Zhaohui [1 ]
Huang, Wenyi [2 ]
Liang, Chen [2 ]
Giles, C. Lee [1 ,2 ]
机构：
[1] Penn State Univ, Comp Sci & Engn, University Pk, PA 16802 USA
[2] Penn State Univ, Informat Sci & Technol, University Pk, PA 16802 USA
来源：
2014 IEEE/ACM JOINT CONFERENCE ON DIGITAL LIBRARIES (JCDL) | 2014年
关键词：
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：
We explore a new metadata extraction framework without human annotators with the ground truth harvested from Web. A new training sample is selected based on not only the uncertainty and representativeness in the unlabeled pool, but also on its availability and credibility in Web knowledge bases. We construct a dataset of 4329 books with valid metadata and evaluate our approach using 5 Web book databases as oracles. Empirical results demonstrate its effectiveness and efficiency.
引用
收藏
页码：141 / 144
页数：4
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