Unstructured data extraction of Chinese expert web page Online publication date: Fri, 31-Oct-2014
by Xudong Hong; Tao Shen; Longhua Shen; Zhengtao Yu; Jianyi Guo
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 7, No. 2, 2014
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.
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