Research of an Algorithm Based on Web Usage Mining
Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the Web data and traces users' visiting characteristics, and then extracts the users' using pattern. This article will study on Web mining algorithm based on usage mining. Through the Web usage mining, enterprise may discover the influence factor of customers' purchase from customers purchase behavior. And it also produces the design mentality of the electronic commerce Website application algorithm. This algorithm is simple, effective and easy to realize, it is suitable to the Web usage mining demand of construct a low cost B2C Website.
In this paper, we provide theoretical analysis for a cubic regularization of Newton method as applied to unconstrained minimization problem. For this scheme, we prove general local convergence results. However, the main contribution of the paper is related to global worst-case complexity bounds for different problem classes including some nonconvex cases. It is shown that the search direction can be computed by standard linear algebra technique.