Grey Wolf Optimizer Based Web usage Data Clustering with Enhanced Fuzzy C Means Algorithm

Recommendation system plays a major role in web mining and it is applied to many applications such as ecommerce, e-government and e-library. The key challenges of recommendation system is to recommend the users based on their interest among more visitors and huge information. To make this challenge effective, there is a need for clustering algorithm to handle the data. Hence, this research focused on designing effective clustering algorithm to apply it in ecommerce applications. The grey wolf optimization based clustering is proposed to make an efficient clustering method for grouping the users based on their interest. To find the effective clustering, proposed a grey wolf optimization based fuzzy clustering algorithm, and made a comparison on Fuzzy C Means (FCM) based Genetic Algorithm (GA), Entropy based FCM and Improved Genetic FCM (FCM-GA). The experimental results proves that it performs better than traditional algorithms, at the same time the quality is improved.