Author(s)

Qingxu Liu, Xiaoqing Xia

Pujiang Institute, Nanjing Tech University, Nanjing, China.

Purpose/Significance: This article constructs a website classification model for academic library websites in Jiangsu. From a quantitative point of view, this paper uses a combination of decision tree algorithm and link analysis method in order to analyze how many categories academic library websites can be divided into? Which indicators can have a greater impact on academic library websites classification? And how the indicators are ranked according to importance. Method/Process: The link analysis method is used to collect the index data of academic library websites in Jiangsu. After the data is cleaned, the decision tree algorithm is used to analyze the data, and the classification decision tree model is constructed. Result/Conclusion: The result shows that academic library websites can be divided into four categories. PC word count, indexed monthly, and Baidu weight have an important influence on the construction of academic library websites’ decision tree. Among the various indicators, the impact of PC word count, mobile word count, Baidu weight, indexed monthly and the rest of others decrease in order.

Academic Library Website, Decision Tree Algorithm, Link Analysis Method, Classification

Liu, Q.X. and Xia, X.Q. (2022) Construction of Classification Model of Academic Library Websites in Jiangsu Based on Decision Tree Algorithm and Link Analysis Method. Open Access Library Journal, 9, 1-9. doi: 10.4236/oalib.1108324.