Review

Research on agricultural search engine optimization

Wang Daoping¹, Wang Ying¹, Liu Guangli^2*, Shen Cuihua² and Liu Tong²

¹University of Science and Technology Beijing, Beijing, 100083 China.

²China Agricultural University, Beijing, 100083 China.

*Corresponding author. E-mail: liugl@cau.edu.cn.

Accepted 7 June, 2010

Abstract

Search engine optimization (SEO) has practical significance for promoting farmers income and agricultural efficiency in China. Firstly, how to extract web page attributes contributed to the ranking in search engine is considered. And the attribute extractor in Java platform is built. Then, a batch gaining method noted AAA is proposed independent of Search Engine API by which a downloader is also designed. Third, a new kernel principal component analysis (KPCA) method is proposed to rank these agricultural web pages on keywords, in which the non-linear combinations of search engine ranking factors can be obtained. By adjusting the kernel function and its parameters in order to ensure maximum contribution rate of variance. Fourth, the software system is developed for agriculture to provide decision support for search engine marketing. Data experimental results show that our method has a good performance.

Key words: Search engine optimization (SEO), kernel principal component analysis (KPCA), attributes extraction.