Commodities Price Dynamic Trend Analysis Based on Web Mining

Abstract

Commodities price of others e-supermarkets or online shopping systems are the most important data for the shopkeepers of shop online. This requirement becomes actuality because of the Web mining developing very fast. The Web mining algorithm from extracting directory tree of different Website, the commodities name on the Web page and commodities price based on participle are described in detailed. All of them depend on the researched of the participle algorithm. The implementation shows that the participle algorithm can get more than ninety nine percent of average full rate and accuracy rate. The error rate of price dynamic trend analysis is less than four percent. The results show as by this way can touch the shopkeepers' minds, and it can support the originality data for the commodities markets and dynamic trend analysis.