Currently it is difficult for search engine to rank effectively.This paper proposes a ranking method of search engines.The method applies collaborative filtering based on the retrieved results from the users in the same community.A parallel algorithm for mining association rules is described to preprocess all users' local directed graphs to find the commonly interesting pages for the users in the same community.Web pages contents

hyperlink structures and the associated texts are then analyzed.Authority pages and hub pages are recognized to discover the related results not found by the search engines.In addition

the evaluation of the web pages is based on not only the hyperlink structures and the query user's evaluation

but also the evaluation of other users in the same community and the usage of the pages by all users.As a result

the ranking method of the search engine is reasonable and effective.