Clustering Algorithm in Data Mining Based on Web Log

Abstract

The advantages of FCM algorithm are that it is mainly applied in point data cluster and can't directly process relational data, for which the paper proposes a clustering algorithm in data mining based on web log . Firstly, the paper improves FCM algorithm which makes it can process relational data, and makes robustness improvement on the algorithm. Then, the traditional FCM algorithm needs to determine in advance on the basis without prior knowledge, for which the paper introduces competition agglomerative algorithm and makes it combine with FCM algorithm, which generates CA-FCM algorithm making it can automatically determine category number of the best classification. The experiments show that mining results of CA-FCM algorithm is close to the mining results of FCM algorithm, and the performance of CA-FCM algorithm is better than that of FCM algorithm when the amount of users access to session is not too much.