Algorithm for Extracting Loosely Structured Data Records Through Digging Strict Patterns

被引：0
|
作者：
Qing Li
Jing Chen
Yipu Wu
机构：
[1] City University of Hong Kong,Department of Computer Science
来源：
World Wide Web | 2009年 / 12卷
关键词：
data extraction; semi-structured data; tree edit distance; content feature; loosely structured data record;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Extracting loosely structured data records (LSDRs) has wide applications in many domains, such as forum pattern recognition, Weblogs data analysis, and books and news review analysis. Yet currently existing methods only work well for strongly structured data records (SDRs). In this paper, we propose to address the problem of extracting LSDRs through mining strict patterns. In our method, we utilize both content feature and tag tree feature to recognize the LSDRs, and propose a new algorithm to extract the Data Records (DRs) automatically. The experimental results demonstrate that our algorithm is able to effectively extract LSDRs with higher precision and recall.
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页码：263 / 284
页数：21
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