A Novel Method for Bilingual Web Page Mining Via Search Engines

A new approach has been developed for acquiring bilingual web pages from the result pages of search engines,which is composed of two challenging tasks.The first task is to detect web records embedded in the result pages automatically via a clustering method of a sample page.Identifying these useful records through the clustering method allows the generation of highly effective features for the next task which is high-quality bilingual web page acquisition.The task of high-quality bilingual web page acquisition is assumed as a classification problem.One advantage of our approach is that it is independent of the search engine and the domain.The test is based on 2 516 records extracted from six search engines automatically and annotated manually,which gets a high precision of 81.3% and a recall of 94.93%.The experimental results indicate that our approach is very effective.