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An Importance Assessment Model of Open-Source Community Java Projects Based on Domain Knowledge Graph

Chengrong Yang1, Rongjing Bu2, Yan Kang2, Yachuan Zhang2, Hao Li2,*, Tao Li2, Junfeng Li2
1 Liupanshui Normal University, Liupanshui, 553000, China
2 Yunnan University, Kunming, 650500, China
* Corresponding Author: Hao Li. Email:

Journal on Big Data 2020, 2(4), 135-144.

Received 20 June 2020; Accepted 25 October 2020; Issue published 24 December 2020


With the rise of open-source software, the social development paradigm occupies an indispensable position in the current software development process. This paper puts forward a variant of the PageRank algorithm to build the importance assessment model, which provides quantifiable importance assessment metrics for new Java projects based on Java open-source projects or components. The critical point of the model is to use crawlers to obtain relevant information about Java open-source projects in the GitHub open-source community to build a domain knowledge graph. According to the three dimensions of the Java opensource project’s project influence, project activity and project popularity, the project is measured. A modified PageRank algorithm is proposed to construct the importance evaluation model. Thereby providing quantifiable importance evaluation indicators for new Java projects based on or components of Java opensource projects. This article evaluates the importance of 4512 Java open-source projects obtained on GitHub and has a good effect.


GitHub open-source community; Java open-source project; domain Knowledge Graph; importance assessment

Cite This Article

C. Yang, R. Bu, Y. Kang, Y. Zhang, H. Li et al., "An importance assessment model of open-source community java projects based on domain knowledge graph," Journal on Big Data, vol. 2, no.4, pp. 135–144, 2020.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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