| dc.contributor.author | Sitanggang, Imas Sukaesih | |
| dc.contributor.author | Husin, Nor Azura | |
| dc.contributor.author | Agustina, Anita | |
| dc.contributor.author | Mahmoodian, Naghmeh | |
| dc.date.accessioned | 2016-06-13T02:57:12Z | |
| dc.date.available | 2016-06-13T02:57:12Z | |
| dc.date.issued | 2010 | |
| dc.identifier.isbn | 978-1-4244-6716-7 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/81043 | |
| dc.description.abstract | Application of data mining techniques in library data
results interesting and useful patterns that can be used to
improve services in university libraries. This paper presents
results of the work in applying the sequential pattern mining
algorithm namely AprioriAll on a library transaction dataset.
Frequent sequential patterns containing book sequences
borrowed by students are generated for minimum supports 0.3,
0.2, 0.15 and 0.1. These patterns can help library in providing
book recommendation to students, conducting book procurement
based on readers need, as well as managing books layout. | id |
| dc.language.iso | en | id |
| dc.publisher | Universiti Teknologi PETRONAS | id |
| dc.title | Sequential Pattern Mining on Library Transaction Data | id |
| dc.type | Article | id |
| dc.subject.keyword | Sequential Pattern Mining | id |
| dc.subject.keyword | AprioriAll | id |
| dc.subject.keyword | Library Transaction Data | id |
