خلاصة:
The purpose of this paper is to study the patron’s usage behavior in an academic library. This study investigates on pattern of patron’s books borrowing in Khunying Long Athakravisunthorn Learning Resources Center, Prince of Songkla University that influence patron’s academic achievement during on academic year 2015-2018. The study collected and analyzed data from the libraries, registrar, and human resources. The students’ performance data was obtained from PSU Student Information System and the rest from ALIST library information system. WEKA was used as the data mining tool employing data mining techniques of association rules and clustering. All data sets were mined and analyzed to identify characteristics of the patron’s book borrowing, to discover the association rules of patron’s interest, and to analyze the relationships between academic library use and undergraduate students’ achievement. The results reveal patterns of patron’s book loan behavior, patterns of book usage, patterns of interest rules with respect to patron’s interest in book borrowing, and patterns of relationships between patron’s borrowing and their grade. The ability to clearly identify and describe library patron’s behavior pattern can help library in managing resources and services more effectively. This study provides a sample model as guideline or campus partnerships and for future collaborations that will take advantage of the academic library information and data mining to improve library management and library services.
ملخص الجهاز:
/niern‹iiic›nnf Journal o]'Injo rinution S‹ ieiice rind 3;funugement Vol. 18, No. 2, 2020, 151-172 Mining and Analyzing Patron's Book-Loan Data and University Data to Understand Library Use Patterns Tipawan Silwattananusarn Department of Library and Information Science Faculty of Humanities and Social Sciences Prince of Songkla University, Pattani Campus Pattani, Thailand Corresponding Author: tipawan.
All data sets were mined and analyzed to identify characteristics of the patron's book borrowing, to discover the association rules of patron's interest, and to analyze the relationships between academic library use and undergraduate students' achievement.
In order to understand students' needs, association rules mining was applied to library circulation data to find interesting rules with respect to users' demands in usage of books (Krishnamurthy & Balasubramani, 2014; Lipeng & Wang, 2015).
The analysis of library and university data using descriptive statistics analysis and correlation analysis in Renaud, Britton, Wang & Ogihara (2015) revealed patterns of library use by academic department, patterns of book usage over 20 years and correlations between library use and grade point average.
Findings from the use of data mining from library management system by €-means algorithm of the cluster analysis (Wang, Tang, Liu & Li, 2011; Hajek & Stejskal, 2014) showed that the cluster results satisfied the demand of the student readers and guided the library to adjust service strategy and provide personalized services.
- Percentage LC category lifespan distribution Predictive Data Mining Model In this part, the questions are “ Mat are the association rules when patrons borrow books?” and “Is there relationship between student academic achievement and theirs book loans?”.
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