Recommendation system using fuzzy C-means clustering

The call for customer with personalized web pages has become loud. To achieve personalized web pages, this study proposes a recommendation system with two approaches on user access behavior by fuzzy clustering method. The aim of this study is to show similar preference to the given users and recommends what they have liked. An empirical case from National Museum of History is illustrated. The recall value was used to evaluate recommended accuracy with two algorithms (item-to-item and user-to-user). It is hopefully that our proposed method may provide valuable information for administrator to manage the web site more efficiency and for users to assess the interested pages more quickly.