Research Of Acquiring Deep Web Forest Products Trading Information

As one of the most important livelihood related resources and productive factors, forest products’ demands are maintaining a steady rapid growth. The popularity of the internet and the acceptance of information technology have provided a new platform for forest products’trade. Thousands of trade markets and forest products trade company websites, online trading platform and forest products trading information websites have provided ordinary users an equal and free way to publish supplying or demanding information. But the information on these web sites can not been indexed by search engines, making it difficult to obtain by ordinary users, on the other hand, these online platforms and websites also have lots of limitations in the classification and organization of information, which prevent the ordinary users from using these information efficiently.A rational classification systems has been represented based on the products categories and codes given by national forest department and the structures of major forest websites. By studying the classifications and structures of existing forest products websites, we classify these websites and different methods have been given to treat these websites, then the "deep web" information can be successfully obtained. This system chooses C#and Python as the two developing languages to capture product information and deploys a combination of database and file to storage product information. This paper concludes some of the problems in this area which have to be improved in the future.