The Library Evaluation Based on the PCA and Fuzzy-c Means
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference（2009）
摘要
As an important library management method the utility and evolution of the library evaluation is much caused from the progression in library circle, and it fits needs to library's management. Based on the development of data mining technology, a Fuzzy-C-Means (FCM) algorithm model is founded to do the library evaluation in this paper, Selecting the Principal component analysis (PCA) to reduce the dimensionality of indexes, and then extract principal components to replace the original indexes, thus reducing the dimensions of the sample input space, at a certain extent improved the accuracy and the classify effect of this algorithm. At last, apply this model to library evaluation, and it shows more generalized performance and better regression accuracy compared with the method of single Fuzzy-c means and BP neural networks.
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关键词
bp neural network,certain extent,fuzzy set theory,library evaluation,library management method,academic libraries,library automation,fuzzy-c means,indexing,library circle,library circle progression,regression accuracy,important library management method,pca,bp neural networks,data mining,algorithm model,principal component analysis,data mining technology,generalized performance,algorithm design and analysis,indexes,neural network,indexation,classification algorithms,principal component,clustering algorithms
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