Volume 29, Issue 4 (12-2023)
Research on Information Science and Public Libraries 2023, 29(4): 446-462 |
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Rostami T, Sohieli F. The transaction analysis of loan and usage of information resources by library members: A case study of public libraries in Ilam province. Research on Information Science and Public Libraries 2023; 29 (4) :446-462
URL: http://publij.ir/article-1-2370-en.html
URL: http://publij.ir/article-1-2370-en.html
Payamenoor University, Tehran, Iran , fsohieli@gmail.com
Abstract: (390 Views)
Purpose: The purpose of this research is to determine the pattern of access to information resources and analysis of loan transactions among users of public libraries in Ilam province using the approach of association rules, clustering and classification in data mining.
Method: In this research, by using data mining techniques, and algorithms of convergence, clustering, and classification rules on data related to the circulation desk of public libraries in Ilam province, the demographic information affecting the study behavior of members and the patterns of using information resources by this heterogeneous community were extracted. The data mining process used in the research (CRISP-DM) consists of six pahses, including business understanding, data understanding, data preparation, modeling (rules of convergence, artificial neural network, and decision tree), evaluation, and deployment, respectively.
Findings: The findings related to different groups using information sources showed that in addition to studying their textbooks, students also studied subjects such as Iranian history and Islamic religion. In terms of gender, women with bachelorʼs degrees were interested in studying Persian language and literature, and fiction. The analysis of resource lending in terms of gender showed that 58 percent of active members of public libraries in Ilam province were women and 42 percent of them were men. This difference shows that women have a greater desire to use the information resources of public libraries in Ilam province. Furthermore, among those who were late in returning their borrowed books, 54 percent were women and 46 percent were men; In terms of returning books on time, women showed their responsibility with 52 percent and men with 48 percent. The results show that men with diplomas were interested in issues related to Islam and this group felt more responsibility for returning their books. In terms of gender and its effect on the studied subjects, undergraduate women, who had free jobs, showed interest in the classes of Persian literature and fiction and did not delay in returning their books. The analysis of the behavior model of the patrons in terms of book return revealed that the men with diploma who had free jobs did not delay in returning loaned books, and the women with diploma and bachelorʼs degrees who had free jobs did not delay in returning loaned books. Moreover, students with undergraduate degrees delayed in returning loaned books. A neural network model was developed to predict the delay in the return of books based on characteristics such as gender and educational level, and the accuracy rate of the model during the learning process with the best prediction accuracy was equal to 69.18%. This shows that it is possible to learn and predict the output by receiving new entries in the database of public libraries of Ilam province.
Originality/value: The deployment of the proposed neural network model on the database of public libraries of Ilam province for predicting the delay in the return of books based on different characteristics, shows that it is possible to learn and predict the output by receiving new entries in the database of these libraries. Moreover, using the association rules technique, it is possible to design a book recommendation system in public libraries of Ilam province.
Method: In this research, by using data mining techniques, and algorithms of convergence, clustering, and classification rules on data related to the circulation desk of public libraries in Ilam province, the demographic information affecting the study behavior of members and the patterns of using information resources by this heterogeneous community were extracted. The data mining process used in the research (CRISP-DM) consists of six pahses, including business understanding, data understanding, data preparation, modeling (rules of convergence, artificial neural network, and decision tree), evaluation, and deployment, respectively.
Findings: The findings related to different groups using information sources showed that in addition to studying their textbooks, students also studied subjects such as Iranian history and Islamic religion. In terms of gender, women with bachelorʼs degrees were interested in studying Persian language and literature, and fiction. The analysis of resource lending in terms of gender showed that 58 percent of active members of public libraries in Ilam province were women and 42 percent of them were men. This difference shows that women have a greater desire to use the information resources of public libraries in Ilam province. Furthermore, among those who were late in returning their borrowed books, 54 percent were women and 46 percent were men; In terms of returning books on time, women showed their responsibility with 52 percent and men with 48 percent. The results show that men with diplomas were interested in issues related to Islam and this group felt more responsibility for returning their books. In terms of gender and its effect on the studied subjects, undergraduate women, who had free jobs, showed interest in the classes of Persian literature and fiction and did not delay in returning their books. The analysis of the behavior model of the patrons in terms of book return revealed that the men with diploma who had free jobs did not delay in returning loaned books, and the women with diploma and bachelorʼs degrees who had free jobs did not delay in returning loaned books. Moreover, students with undergraduate degrees delayed in returning loaned books. A neural network model was developed to predict the delay in the return of books based on characteristics such as gender and educational level, and the accuracy rate of the model during the learning process with the best prediction accuracy was equal to 69.18%. This shows that it is possible to learn and predict the output by receiving new entries in the database of public libraries of Ilam province.
Originality/value: The deployment of the proposed neural network model on the database of public libraries of Ilam province for predicting the delay in the return of books based on different characteristics, shows that it is possible to learn and predict the output by receiving new entries in the database of these libraries. Moreover, using the association rules technique, it is possible to design a book recommendation system in public libraries of Ilam province.
Type of Study: quantitative |
Subject:
Management and Evaluation of Libraries
Received: 2022/11/24 | Accepted: 2023/05/31 | Published: 2023/12/31
Received: 2022/11/24 | Accepted: 2023/05/31 | Published: 2023/12/31
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