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Improving Book Lending Service in UTM Library with Apriori Rule-mining

Erschienen am 19.12.2018, 1. Auflage 2018
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ISBN/EAN: 9786139956753
Sprache: Englisch
Umfang: 148 S.
Format (T/L/B): 0.9 x 22 x 15 cm
Einband: kartoniertes Buch

Beschreibung

The use of data mining techniques to improve information system services is an ongoing research area that has gained immense attention. Academic libraries in institutions of higher learning are not left out in the quest to continuously support and provide meaningful services to their growing user base whose dependence on reliable services has increased exponentially. However, the proliferation of e-libraries, social media, commercial information providers and new publishing paradigms which seeks to provide free scholarly materials for reuse, revision, remix and redistribution challenge the academic librarys role as a pacesetter. This puts the latter under pressure to evolve and yield better ways of leading scholarship and maintaining patronage from everyone in the academic environment. Thus, this book reviews a set of factors influencing book lending among patrons and also discusses a data mining technique called association rule mining (ARM). It employs the use of Apriori ARM algorithm to build a recommender system which gives the academic libraries a leverage over its rivals as seen in the research findings and user acceptance testing results.

Autorenportrait

Dr. Habeeb Omotunde bagged a doctorate degree from UTHM, Malaysia in 2018. After completing his Bachelor's and Master's degrees with distinction, he has worked with professionals in the Education, Banking & Telecommunications sector using Oracle technologies. His research interests include Data Mining, Hybrid Threat Modeling & Software Security.

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