Information Fusion For The Internet Market In The Main Study

With the rapid development of online drug market, a large amount of illegal drug information appears on internet due to the backwardness of online product monitoring means and techniques. The illegal information should be monitored by the online product monitoring engine and the market subject of the drug information should be tracked as well. Firstly, the information fusion of online product subject information should integrate the information distributed on the internet and different monitoring departments. Secondly, expert knowledge should be fully utilized to determine the category of illegal online drug information. As a result of heterogeneity of network resources, information fusion systems have to integrate and combine the multi-source data and information and reduce the ambiguity. Inconsistency and incompleteness leads to uncertainty in the information fusion procedure due to subjectivity and ambiguity of the expert knowledge.A web information fusion architecture combining uncertainty reduction is proposed for the online market subject information extraction and fusion process, making up the defect on uncertainty processing of traditional knowledge systems. The subjectivity of the initial setup of the certainty factor and subjective Bayesian is reduced by the feedback and self-adaption mechanism. The system is then applied to the online drug subject tracking problem, which solves the redundancy and contradiction in the drug subject fusion procedure and subjectivity and ambiguity of expert knowledge, thus provides reliable illegal market subject information for the online drug supervisory department.