[Purpose/significance] Studies on recommender systems in the library field have been mostly focused on theoretical models or technical constructions. They lack data of the current status and real practical issues. This paper aims to investigate the application situation and existing problems of the recommender system in university libraries in order to put forward references for enhancing libraries' knowledge services. [Method/process] Based on website visits and the questionnaire survey of 116 universities included in the "211 Project", data were processed through classified statistics and comparative analysis. [Result/conclusion] The results show that almost all the university libraries offer non-personalized recommender services, and 63% of them provide personalized recommender services. Various recommender systems with diverse services are widely emerging, which reflects great needs for smart knowledge discovery and delivery services. 79% of the university libraries actively seek cooperation with other platforms to broaden their recommending capacities. More personalized recommender systems and systematic and intelligent services are still in demands. In addition, libraries need to pay more attention to readers' satisfaction on the recommender systems, as well as their privacy issues.
Li Min
,
Wang Yingchun
,
Liu Yanquan
. An Analytical Survey of Recommender Systems in China's “211 Project” University Libraries[J]. Library and Information Service, 2016
, 60(9)
: 55
-60
.
DOI: 10.13266/j.issn.0252-3116.2016.09.008
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