|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|106231||2018||8 صفحه PDF||سفارش دهید||3702 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Procedia Manufacturing, Volume 22, 2018, Pages 550-557
Recommender systems are important tools in library websites that assists the user to find the appropriate books. With the rapid development of internet technologies and the number of books has varied which waste of time and difficulty for finding from library searching system. This research presents a book recommendation system for university libraries to support user interests which are related in the same topic and faculty. The main motive of this research is to develop the technique which recommends the most suitable books to users according to the faculty of the user profile with book category, and book loan or FUCL technique. This is based on the combined features of association rule mining. The results show that FUCL mining technique is suitable to apply for the recommender book tool in the library and has a higher accuracy value than other technique.