An average linear time algorithm for web usage mining

In this paper we study the complexity of a data mining algorithm for extracting patterns from user web navigation data that was proposed in previous work [3]. The user web navigation sessions are inferred from log data and modeled as a Markov chain. The chain’s higher probability 1 trails correspond to the preferred trails on the web site. The algorithm implements a depth-first search that scans the Markov chain for the high probability trails. We show that the average behaviour of the algorithm is linear time in the number of web pages accessed. Keywords.Web usage mining, Markov chains, analysis of algorithms