Using Association Rules to Discover Book Recommendations for Library Readers
| Autor: | LIN,TAI-YAN, 林泰言 |
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| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 In the past、libraries』 records only record whether books have been returned or not. These records will not be stored after borrowers have returned the books. However、due to the advances of technology in recent years、borrower’s records can now be easily recorded and stored at the same time. These records become larger as time progresses. Nowadays、in order to improve its utility rate、libraries have evolved to actively recommending which books to read. This is done by associating the interests of readers to types of books available. The purpose of this study is to improve the libraries』 utility rate by using Data Mining to find readers』 implied associations from the large database and apply the mining’s result to recommend suitable books for readers accordingly. 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 for the books. 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 personalized service to the library、can offer very useful reference information. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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