2 research outputs found
Mining and Analyzing Patron's Book-Loan Data and University Data to Understand Library Use Patterns
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.Comment: 22 pages, 9 figure
Mining and Analyzing Patron’s Book-Loan Data and University Data to Understand Library Use Patterns
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