A new efficient approach for data clustering in electronic library using ant colony clustering algorithm

An-Pin Chen*, Chia Chen Chen

*此作品的通信作者

研究成果: Article同行評審

20 引文 斯高帕斯(Scopus)

摘要

Purpose - Traditional library catalogs have become inefficient and inconvenient in assisting library users. Readers may spend much time in searching library materials via printed catalogs. Readers need an intelligent and innovative solution to overcome this problem. The purpose of this paper is to illustrate how data mining technology is a good approach to fulfill readers' requirements. Design/methodology/approach - Data mining is considered to be the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. This paper analyzes the readers' borrowing records by using the following techniques: data analysis, building data warehouse and data mining. Findings - The mining results show that all readers can be categorized into five clusters, and each cluster has its own characteristics. It was also found that the frequency for graduates and associate researchers to borrow multimedia data is much higher. This phenomenon shows that these readers have a higher preference for accepting digitized publication. Besides, we notice that more readers borrow multimedia data rise in years. This up trend indicates that readers are gradually shifting their preference in reading digital publications. Originality/value - The paper proposes a technique to discover clusters by using ant colony methods.

原文English
頁(從 - 到)548-559
頁數12
期刊Electronic Library
24
發行號4
DOIs
出版狀態Published - 2006

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