Using data mining techniques to predict user’s behavior and create recommender systems in the libraries and information centers
Global Knowledge, Memory and Communication
ISSN: 2514-9342
Article publication date: 30 October 2020
Issue publication date: 27 July 2021
Abstract
Purpose
This study aims to analyze and predict a user’s behavior and create recommender systems in libraries and information centers, using data mining techniques.
Design/methodology/approach
The present study is an analytical survey study of cross-sectional type. The required data for this study were collected from the transactions of the users of libraries and information centers in Hamadan University of Medical Sciences. Using data mining techniques, the existing patterns were investigated, and users’ loan transactions were analyzed.
Findings
The findings showed that the association rules with the degree of confidence above 0.50 were able to determine user access patterns. Furthermore, among the decision tree algorithms, the C.05 predicted the loan period, referrals and users’ delay with the highest accuracy (i.e. 90.1). The other findings on feedforward neural network with R = 0.99 showed that the predicted results of neural network computation were very close to the real situation and had a proper estimation of user’s delay prediction. Finally, the clustering technique with the k-means algorithm predicted users’ behavior model regarding their loyalty.
Practical implications
The results of this study can lead to providing effective services and improve the quality of interaction between librarians and users and provide a good opportunity for managers to align supply of information resources with the real needs of users.
Originality/value
The results of the study showed that various data mining techniques are applicable with high efficiency and accuracy in analyzing library and information centers data and can be used to predict a user’s behavior and create recommendation systems.
Keywords
Acknowledgements
This paper was extracted from master’s thesis by the ethic code of IR.UMSHA.REC.1396.27. The authors gratefully acknowledge the Vice-chancellor for Research and Technology in Hamadan University of Medical Sciences for supporting this study and also the esteemed director of libraries and information centers in Hamadan University of Medical Sciences, regarding the availability of data related to the users’ transactions.
Citation
Ansari, N., Vakilimofrad, H., Mansoorizadeh, M. and Amiri, M.R. (2021), "Using data mining techniques to predict user’s behavior and create recommender systems in the libraries and information centers", Global Knowledge, Memory and Communication, Vol. 70 No. 6/7, pp. 538-557. https://doi.org/10.1108/GKMC-04-2020-0058
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited