Using data mining technology to solve classification problems. A case study of campus digital library

Date01 May 2006
Published date01 May 2006
AuthorChan‐Chine Chang,Ruey‐Shun Chen
Subject MatterInformation & knowledge management,Library & information science
Using data mining technology to
solve classification problems
A case study of campus digital library
Chan-Chine Chang and Ruey-Shun Chen
Institute of Information Management, National Chiao Tung University,
Hsinchu, Taiwan
Purpose – Traditional library catalogs have become inefficient and inconvenient in assisting library
users. Readers may spend a lot of time searching library materials via printed catalogs. Readers need
an intelligent and innovative solution to overcome this problem. The paper seeks to examine data
mining technology which is a good approach to fulfill readers’ requirements.
Design/methodology/approach – Data mining is considered to be the non-trivial extraction of
implicit, previously unknown, and potentially useful information from data. This paper analyzes
readers’ borrowing records using the techniques of data analysis, building a data warehouse, and data
Findings – The paper finds that after mining data, readers can be classified into different groups
according to the publications in which they are interested. Some people on the campus also have a
greater preference for multimedia data.
Originality/value – The data mining results shows that all readers can be categorized into five
clusters, and each cluster has its own characteristics. The frequency with which graduates and
associate researchers borrow multimedia data is much higher. This phenomenon shows that these
readers have a higher preference for accepting digitized publications. Also, the number of readers
borrowing multimedia data has increased over the years. This trend indicates that readers preferences
are gradually shifting towards reading digital publications.
Keywords Digital libraries,Electronic publishing, Knowledge mining, Multimedia
Paper type Case study
1. Introduction
The traditional library cannot satisfy customers with the same speed and
convenience as a library with a computerized system (Yu and Chen, 2001).
Therefore, it is essential that libraries have a smart and efficient way to help readers
find useful books. Data mining is an important new information technology used to
identify significant data from vast amounts of records. In other words, it is the
process of exposing important hidden patterns in a set of data. It is also part of a
process called knowledge discovery in databases, which presents and processes data
to obtain knowledge. The usefulness of data mining is that it proactively seeks out
trends within an industry and provides useful outcomes to organizations that
maintain substantial amounts of information.
The goal of data mining is to improve the quality of the interaction between the
library and its users. The collected data contain valuable information that can be
integrated into the library’s strategy, and can be used to improve library decisions. We
need an automatic analysis and discovery tool for extracting useful knowledge from
huge amounts of raw library data. Knowledge discovery in databases and the data
The current issue and full text archive of this journal is available at
Using data
The Electronic Library
Vol. 24 No. 3, 2006
pp. 307-321
qEmerald Group Publishing Limited
DOI 10.1108/02640470610671178

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