[Objective] This paper studies the navigation features of top academic library websites from the United States, aiming to improve the services of their Chinese counterparts. [Methods] First, we identified library websites of the top 15 U.S. universities and downloaded their navigation texts. Second, we analyzed the similarities and differences among these texts with tag cloud and Vector Space Model. Finally, we examined our findings with the “2016 State of America’s Libraries Report”. [Results] The proposed method was intuitive and generated analysis results fast, which could be further processed with text mining techniques. [Limitations] Only retrieved the first and, second levels of navigation as well as titles of the homepages. [Conclusions] The proposed model provides useful information for the academic libraries in China.
尹相权, 李书宁. 基于VSM的美国一流大学图书馆网站导航文本调查与分析[J]. 数据分析与知识发现, 2017, 1(3): 90-95.
Yin Xiangquan,Li Shuning. Analyzing Website Navigation Features of Top U.S. Academic Libraries. Data Analysis and Knowledge Discovery, 2017, 1(3): 90-95.
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