An incremental data mining algorithm for discovering web access patterns

Mining frequent traversal patterns is to discover the reference paths traversed by a sufficient number of users from web logs, which can be used for prefetching and suggestion for web users. However, the discovered frequent traversal patterns may become invalid or inappropriate when the user behaviours are changed. In this paper, we propose an incremental updating technique to maintain the discovered frequent traversal patterns when the traversal paths are inserted into or deleted from the database. The experimental results show that our algorithms are more efficient than other algorithms for the maintenance of mining frequent traversal patterns.