Using Clustering Techniques to Discover the Recommendation Services of Borrowing Books for Libraries

• Main Authors: Jerry Huang, 黃俊榮
• Other Authors: 陳垂呈
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/83041893230825617362

碩士 === 南台科技大學 === 資訊管理系 === 94 === The fast development in economy of cause in recent years, the collected books amount of the library is increasing fast too, find the books which accord with reader's demand in these a large amount of collected books, it is more and more difficult. So, how can offer the information of the collected books according to reader's need, have already become an important subject of the library at present. On the other hand, the library hopes to offer more information and service to readers too, hope that the collection in the library can try one's best to be utilized effectively , in order to enable reader to obtain benefit most from the book borrowed. In this thesis, we according to borrowing database of library of Southern Taiwan University of Technology offered, and regard borrowing the data of readers as the data source mined, every one borrows data includes books and one degree of value of interest that readers once borrowed, look for adaptive books for readers,and look for adaptive readers for the books. Utilize clustering of the data mining approach come the books or readers, through calculation of the borrowing similar degree, look for adaptive reader or books of group and recommend it . Finally, according to the method put forward, we design and build a recommend system of adaptive books and reader. The result of mining, while planning reader's personalised service to the library, can offer very useful reference information .