Paper Title
Recommendation Services of Academic Contents Based on Users’ Frequency of Use

Various kinds of information are nowadays indiscriminately available; hence, it is important to reveal users’ requirements and to provide them with the appropriate data in order to efficiently operate systems that provide services based on previous reactions and activities of users. Therefore, this study proposes a method that provides personalized recommendation services and customized information to users by using not only basic information but also frequency of use in log data. Index Terms - Personalization, Recommendation, Frequency Of Use, Collaborative Filtering, Association Rules, Academic Content