[Purpose/significance] The inter-library loaning (ILL) service is essential to multi-academic campus universities' library. By using ILL data, the paper will build a dynamic collection optimizing mode based on readers' demands.[Method/process] Firstly it examined the status quo and methods of ILL. Then, some results of bipartite matching and recommendation such as network-based inferencing (NBI) were referred to. Based on these, it built a model aiming to optimize collections of academic libraries. With the loaning data of Soochow University library during 2013 as the training data, an optimizing case was performed. 2469 of the inter-library loaning data during 2014 was used for testing the model's effects.[Result/conclusion] Through the optimization of the collection,the efficiency of using could be improved and the delivery cost will be reduced.
Li Zhuozhuo
,
Ma Yue
,
Han Jingxian
. The Collection Optimization of Inter-library Lending Based on Bipartite Matching:A Case Study of Soochow University[J]. Library and Information Service, 2017
, 61(19)
: 80
-88
.
DOI: 10.13266/j.issn.0252-3116.2017.19.010
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