Application of Clustering Analysis Algorithm in Digital Library

DOI

10.2991/emcs-15.2015.29How to use a DOI?

Keywords

Clustering Analysis; K-means; Algorithm; Digital Library; Resource Analysis

Abstract

Clustering analysis embarks from the data itself to dig out the internal feature relations of the data and present the category information the data contains. Of the clustering methods, hierarchical clustering method, K-Means method, etc. are frequently used. Taking the example of classifying 22 categories of library collections, this work exploits the application of clustering analysis algorithm in digital library with the use of K-means algorithm and the library collection data like book use rate and collection proportion. The data used in this work comes from the book management system of Jianghan University. Data processing is done with the SPSS software. 22 categories of library collections are classified into four categories. They are Unnoticed, Shortage in resource allocation, Reasonable resource allocation and Partial-saturation in resource allocation. The high reliability and stability of K-Means clustering algorithm are exploited and verified after applying it to resource analysis of digital library, providing scientific basis for the construction and evaluation of library collection resource.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yan Ge
PY  - 2015/01
DA  - 2015/01
TI  - Application of Clustering Analysis Algorithm in Digital Library
BT  - Proceedings of the International Conference on Education, Management, Commerce and Society
PB  - Atlantis Press
SP  - 133
EP  - 137
SN  - 2352-5398
UR  - https://doi.org/10.2991/emcs-15.2015.29
DO  - 10.2991/emcs-15.2015.29
ID  - Ge2015/01
ER  -