Construction and Application of the User Behavior Knowledge Graph in Software Platforms

Authors

  • Fuhua Shang School of Computer and Information Technology, Northeast Petroleum University, China
  • Qiuyu Ding School of Computer and Information Technology, Northeast Petroleum University, China
  • Ruishan Du School of Computer and Information Technology, Northeast Petroleum University, China
  • Maojun Cao School of Computer and Information Technology, Northeast Petroleum University, China
  • Huanyu Chen School of Computer and Information Technology, Northeast Petroleum University, China

DOI:

https://doi.org/10.13052/jwe1540-9589.2027

Keywords:

User behavior knowledge graph, user knowledge extraction, graph database, knowledge graph construction

Abstract

The analysis of user behavior provides a large amount of useful information. After being extracted, this information is called user knowledge. User knowledge plays a guiding role in implementing user-centric updates for software platforms. A good representation and application of user knowledge can accelerate the development of a software platform and improve its quality. This paper aims to further the utilization of user knowledge by mining the user knowledge that is implicit in user behavior and then constructing a knowledge graph of this behavior. First, the association between a software bug and a software component is mined from the user knowledge. Then, the knowledge entity extraction and relationship extraction are performed from the development code and the user behavior. Finally, the knowledge is stored in the graph database, from which it can be visually retrieved. Relevant experiments on CIFLog, an integrated logging processing software platform, have proved the effectiveness of this research. Constructing a user behavior knowledge graph can improve the utilization of user knowledge as well as the quality of software platform development.

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Author Biographies

Fuhua Shang, School of Computer and Information Technology, Northeast Petroleum University, China

Fuhua Shang is a professor at the School of Computer and Information Technology, Northeast Petroleum University. He is a senior member of China Computer Federation. He received his M.S. in Computer Application from Harbin Institute of Technology, China in 1990 and a Ph.D. degree in Computer Major from Harbin Institute of Technology, China in 2007. His main research areas include artificial intelligence, knowledge representation, and deep learning.

Qiuyu Ding, School of Computer and Information Technology, Northeast Petroleum University, China

Qiuyu Ding is a Ph.D. candidate at Harbin Institute of Technology, China. She received her B.S. in Computer Science and Technology from Northeast Petroleum University, China in 2017, and purchase an M.S. in Software Engineering from there in 2020. Her main research directions include natural language processing, knowledge representation, and artificial intelligence.

Ruishan Du, School of Computer and Information Technology, Northeast Petroleum University, China

Ruishan Du is an associate professor at the School of Computer and Information Technology at Northeast Petroleum University. He received his M.S. degree from Northeast Petroleum University in 2007 and is currently studying for his doctorate there. His main research areas include artificial intelligence, knowledge graph, and deep learning.

Maojun Cao, School of Computer and Information Technology, Northeast Petroleum University, China

Maojun Cao, associate professor, received his M.S. degree in computer engineering from Northeast Petroleum University in 2008 and his Ph.D. in earth exploration and information technology from China Petroleum Exploration and Development Research Institute in 2018. Focusing on the field of oil and gas logging processing interpretation and artificial intelligence for 15 years, he also studies software engineering and large-scale software platform development, logging processing and interpretation software and 3D attribute modeling, knowledge mapping, etc.

Huanyu Chen, School of Computer and Information Technology, Northeast Petroleum University, China

Huanyu Chen is a M.S. candidate at Northeast Petroleum University, China. He received his B.A. degree in 2014 from Northeast Petroleum University. His main research areas include machine learning and knowledge graph.

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Published

2021-03-16

How to Cite

Shang, F. ., Ding, Q. ., Du, R., Cao, M. ., & Chen, H. . (2021). Construction and Application of the User Behavior Knowledge Graph in Software Platforms. Journal of Web Engineering, 20(2), 387–412. https://doi.org/10.13052/jwe1540-9589.2027

Issue

2021: Vol 20 Iss 2

Section

Advanced Practice in Web Engineering