Mining Sequence Patterns in Evolving Databases

In many applications, the content of a database changes over time. For example, new customer sequences are periodically added to a bookstore’s database as the store attracts new customers. Similarly, every visit to a Web site will add a new log to the site’s log database. There are also situations in which we have to delete sequences from the database. As an example, when mining current access patterns of a Web site, we may need to delete some out-of-date logs such as those that are more than a year old. Since an operational database changes continuously, the set of frequent sequences has to be updated incrementally. One simple strategy is to apply an existing mining algorithm on the updated database. However, this strategy fails to take advantage of the valuable information obtained from a previous mining exercise. We note that this inforIGI PUBLISHING