Automatic Data Records Extraction from List Page in Deep Web Sources

被引：0
|
作者：
Chen Hong-ping [1 ]
Fang Wei [1 ]
Yang Zhou [1 ]
Zhuo Lin [1 ]
Cui Zhi-Ming [1 ]
机构：
[1] Soochow Univ, Inst Intelligent Informat Proc & Applicat, Suzhou, Jiangsu, Peoples R China
来源：
2009 ASIA-PACIFIC CONFERENCE ON INFORMATION PROCESSING (APCIP 2009), VOL 1, PROCEEDINGS | 2009年
关键词：
Data record; Data Extraction; Deep Web;
D O I：
10.1109/APCIP.2009.100
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
with the explosive growth and popularity of the World Wide Web, a wealth of online e-commerce information resources become available. List pages in these web sites are usually automatically generated from the back-end DBMS using scripts. In order to provide value-added services and convenience for users, it is very necessary to integrate web sources of the same domain. Given the huge number of these web pages, it is difficult and even impossible to use a manual approach to extract data records from these list pages on a large scale. According to characteristics of the template-based list pages, in this paper, we propose a LBDRF algorithm to solve the problem of automatic data records extraction from web pages in Deep Web. Our experimental results show that the proposed method performs well.
引用
收藏
页码：370 / 373
页数：4
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