Sequential pattern mining on library transaction data

Citation

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. .

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.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Computer Science and Information Technology
DOI Number:	https://doi.org/10.1109/ITSIM.2010.5561316
Publisher:	IEEE
Keywords:	Sequential pattern mining; AprioriAll; Library transaction data
Depositing User:	Nabilah Mustapa
Date Deposited:	08 Jul 2019 02:45
Last Modified:	08 Jul 2019 02:45
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ITSIM.2010.5561316
URI:	http://psasir.upm.edu.my/id/eprint/69676
Statistic Details:	View Download Statistic

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