Research Of Text Information Filtering In Forest Product Trade Information Recommendation

Information push service has been widely applied to various e-commerce sites. Information push service could initiatively provide useful information for the users. And it has the advantages of initiative and personality. The forest products trading information has the characters of strong field, short documents, the information user is also a provider. The users of forest products trading have the characters of strong purchase purpose and fixed field. When using the traditional information push technique to provide personalized information services, it cannot fully meet the characteristics of the forest products trading.The vector space model of forest products trading information is built up on the base of analyzing the features of forest products trading information. The forest products trading information users’ interest feature model is built up on the base of analyzing the users’features. On the base of analyzing the features of forest products trading information filtering process, the cascade filtering technique has been brought up to exactly meet the users’needs. It is brought up by strictly filtering the user’s dominant needs firstly, roughly filtering the user’s dominant needs secondly, filtering the user’s implicit needs finally. A filter mechanism was established under the system implementation environment.The experimental results show the cascade filtering technique can efficiently filter the user’s satisfied information. Conclusion of the paper sums up the main research achievements and carried out some potential reaserch directions in the future.