Extracting loosely structured data records through mining strict patterns

被引：4
|
作者：
Wu, Yipu [1 ]
Chen, Jing [1 ]
Li, Qing [1 ]
机构：
[1] City Univ Hong Kong, Dept Comp Sci, 83 Tat Chee Avenne, Kowloon, Hong Kong, Peoples R China
来源：
2008 IEEE 24TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3 | 2008年
关键词：
D O I：
10.1109/ICDE.2008.4497543
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Extracting loosely structured data records (DRs) has wide applications in many domains, such as forum pattern recognition, blog data analysis, and books and news review analysis. Currently existing methods work well for strongly structured DRs only. In this paper, we address the problem of extracting loosely structured DRs through mining strict patterns. In our method, we utilize both content feature and tag tree feature to recognize the loosely structured DRs, and propose a new approach to extract the DRs automatically. Through experimental study we demonstrate that this method is both effective and robust in practice.
引用
收藏
页码：1322 / +
页数：2
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