Paper Info
Title
Unstructured data extraction of Chinese expert web page
Abstract
Aiming at the problem of requiring a lot of human intervention in the process of unstructured data extraction from expert page based on traditional extraction methods, this paper proposes a method which detects data template automatically based on similarities and differences between HTML tags and strings, uses the lattice theory to find the location of the data grid region storing unstructured expert data, thus accesses to unstructured expert data. Firstly, with the help of the classifier on Chinese Expert Entity Homepages, a lot of expert pages are acquired by expert web crawler. Secondly, divide the expert pages into two types, list type and document type, then extract respectively the unstructured data from the two different types. Lastly, the extraction experiments are conducted on different types of web pages by improving open source code of Roadrunner. Experimental results show that, in the case of unsupervised, this method performs effectively on extraction of unstructured web data from Chinese expert pages.
Year
DOI
Venue
2014
10.1504/IJWMC.2014.059709
IJWMC
Keywords
Field
DocType
chinese expert web page,extraction experiment,chinese expert page,expert page,unstructured data,different type,unstructured web data,expert web crawler,data grid region,unstructured expert data,unstructured data extraction,lattice theory
HTML element,Data mining,Information retrieval,Web page,Computer science,Data grid,Unstructured data,Roadrunner,Classifier (linguistics),Web crawler,Document type definition,Distributed computing
Journal
Volume
Issue
Citations 
7
2
0
PageRank 
References 
Authors
0.34
5
5
Name
Order
Citations
PageRank
Xudong Hong163.53
Tao Shen200.34
Longhua Shen300.68
Zhengtao Yu446069.08
Jianyi Guo52010.99