Deep Web query interface identification based on decision tree and link-similar
基于决策树和链接相似的Deep Web查询接口判定*

In order to solve the problems existed in the traditional method that Deep Web query interfaces are more false positives and search engine class interface can not be effectively distinguished, this paper proposed a Deep Web query interface identification method based on decision tree and link-similar. This method used attribute information gain ratio as selection level, built a decision tree to pre-determine the form of the interfaces to identify the most interfaces which had some distinct features, and then used a new method based on link-similar to identify these unidentified again, distinguishing between Deep Web query interface and the interface of search engines. The result of experiment shows that it can enhance the accuracy and proves that it is better than the traditional methods.