Advertisements on the Web, rising as a major profit source of Web services, have a distinctive characteristic of detailed classification of potential customers, compared with those of other conventional media such as TV and newspaper. It is therefore possible to advertise selectively according to personal characteristics and to record precise advertisement effects. Web-based advertisement management systems of nowadays have the capability to select ones compatible with personal environment characteristics and registered information, and to provide processed information and knowledge about advertisement effects based on usage recordings. However, they have severe problems in modeling diverse requirements or characteristics of users : customers, advertisers and ISP, and in matching and coordinating of them. In order to solve these problems, we propose a frame work for coordinating the needs of users, advertisers, and ISPs, which is built on top of tree-style classification of advertisements. Other schemes are supported around the framework as follows : (1) characteristics management of pages within themselves, (2) rule-based modeling of advertisement target, and (3) user modeling and case-based analysis. We propose a prototype system within the framework.