[Purpose/significance] Based on the established evaluation indexes for the library outcomes (performances), the projection pursuit clustering (PPC) model is applied to evaluate the library outcomes (performances), to clarify the influence relationship between the evaluation index and the library outcomes (performances), to rank the library outcomes (performances), and thus to put forward the measurement improving the library outcomes (performances).[Method/process] According to the collected sample data of the library outcomes (performances), the Matlab program of the PPC model based on swarm intelligence crow search algorithm is developed. The reasonable cutoff value is taken. The PPC model of the library outcomes (performances) with the real global optimization, the projection vector as well as its coefficient, and the projection value of the samples are established.[Result/conclusion] The projection vector coefficient of each evaluation index and the evaluation function or the scores of the library outcomes (performances) are simultaneously obtained by optimizing the PPC model. The PPC model possesses the characteristics of the simple structure, the good objective, the clear mathematical meaning, and the good convenience to apply the PPC model. The rank and the classification of the library outcomes (performances) using PPC model are good agreement with the results according to the experts. It is approved that the PPC model is applicable, effective and a new method to the library outcomes (performances) evaluation.
Lou Wengao
,
Gan Ruijuan
,
Li Tan
. The Library Outcomes (Performances) Evaluation Using the Projection Pursuit Clustering Model[J]. Library and Information Service, 2017
, 61(9)
: 65
-73
.
DOI: 10.13266/j.issn.0252-3116.2017.09.008
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