Design and Implementation of k-most Library Users Mining

Since library storage has been increasing day by day, it is difficult for readers to find the books which interest them as well as representative booklists. How to utilize meaningful information effectively to improve the service quality of the digital library appears to be very important. The process considered not only the relationship of a cluster of users but also the associations among the information accessed. This paper not only constructs a recommendation service for readers to search books from the web but takes the initiative in finding the most suitable books for readers as well. Furthermore, library managers are expected to purchase core and hot books from a limited budget to maintain and satisfy the requirements of readers along with promoting digital library services. The experimental results of association rule mining in academic libraries revealed interesting rules with respect to users interest in usage of books. The rules also help the institutions for arriving decision related to investment of budget for specific books titles.