Sequential pattern mining on library transaction data
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....
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2010
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/69676/ http://psasir.upm.edu.my/id/eprint/69676/1/Sequential%20pattern%20mining%20on%20library%20transaction%20data.pdf |
| _version_ | 1848856475502379008 |
|---|---|
| author | Sitanggang, Imas Sukaesih Husin, Nor Azura Agustina, Anita Mahmoodian, Naghmeh |
| author_facet | Sitanggang, Imas Sukaesih Husin, Nor Azura Agustina, Anita Mahmoodian, Naghmeh |
| author_sort | Sitanggang, Imas Sukaesih |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T11:42:15Z |
| format | Conference or Workshop Item |
| id | upm-69676 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:42:15Z |
| publishDate | 2010 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-696762019-07-08T02:45:09Z http://psasir.upm.edu.my/id/eprint/69676/ Sequential pattern mining on library transaction data Sitanggang, Imas Sukaesih Husin, Nor Azura Agustina, Anita Mahmoodian, Naghmeh 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. IEEE 2010 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69676/1/Sequential%20pattern%20mining%20on%20library%20transaction%20data.pdf Sitanggang, Imas Sukaesih and Husin, Nor Azura and Agustina, Anita and Mahmoodian, Naghmeh (2010) Sequential pattern mining on library transaction data. In: International Symposium on Information Technology (ITSim'10), 15-17 June 2010, Kuala Lumpur Convention Centre, Kuala Lumpur. . 10.1109/ITSIM.2010.5561316 |
| spellingShingle | Sitanggang, Imas Sukaesih Husin, Nor Azura Agustina, Anita Mahmoodian, Naghmeh Sequential pattern mining on library transaction data |
| title | Sequential pattern mining on library transaction data |
| title_full | Sequential pattern mining on library transaction data |
| title_fullStr | Sequential pattern mining on library transaction data |
| title_full_unstemmed | Sequential pattern mining on library transaction data |
| title_short | Sequential pattern mining on library transaction data |
| title_sort | sequential pattern mining on library transaction data |
| url | http://psasir.upm.edu.my/id/eprint/69676/ http://psasir.upm.edu.my/id/eprint/69676/ http://psasir.upm.edu.my/id/eprint/69676/1/Sequential%20pattern%20mining%20on%20library%20transaction%20data.pdf |