Discovering classification rules [MAR96,CS96,HCC93,WK91] allows one to develop a profile of items belonging to a particular group according to their common attributes. This profile can then be used to classify new data items that are added to the database. In Web mining, classification techniques allow one to develop a profile for clients who access particular server files based on demographic information available on those clients, or based on their access patterns. For example classification on WWW access logs may lead to the discovery of relationships such as the following:
In some cases, valuable information about clients can be gathered by the server automatically from the client browsers. This includes information available on the client side in the history files, cookie files, etc. Other methods used to obtain profile and demographic information on clients include user registration, online survey forms, and techniques such as ``anonymous ticketing" [Inc96].
Clustering analysis [KR90,Fis95,NH94] allows one to group together clients or data items that have similar characteristics. Clustering of client information or data items on Web transaction logs, can facilitate the development and execution of future marketing strategies, both online and off-line, such as automated return mail to clients falling within a certain cluster, or dynamically changing a particular site for a client, on a return visit, based on past classification of that client.