In this paper, we present an Intelligent Cluster Search Engine System, called ICSE. This system is motivated by the observation that traditional search engines present to the users a set of non-classified web pages based on its ranking mechanism, and the unfortunate results are that they usually can not satisfy the need of users. For this reason, ICSE provides to the user a set taxonomic web pages in response to a user's query, and thus it would greatly help the users filter out irrelevant or redundant information. The proposed system can be divided into two parts. The first is the knowledge base constructed by Open Directory Project and Yahoo! Directory. The second is the fast clustering algorithm described herein for clustering the web pages. In addition, in response to a user's query, the proposed system will first send the query to a meta-search engine. Then, it will create a clustered document set using the given knowledge base and the clustering algorithm of ICSE. Our simulation result showed that the proposed system can enhance the relevance and coverage of the search results that the users need compared with traditional search engines.