標題: A new efficient approach for data clustering in electronic library using ant colony clustering algorithm
作者: Chen, An-Pin
Chen, Chia- Chen
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: digital libraries;cluster analysis;data collection;data analysis
公開日期: 2006
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.
URI: http://hdl.handle.net/11536/14375
http://dx.doi.org/10.1108/02640470610689223
ISSN: 0264-0473
DOI: 10.1108/02640470610689223
期刊: ELECTRONIC LIBRARY
Volume: 24
Issue: 4
起始頁: 548
結束頁: 559
Appears in Collections:Articles


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