Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (5): 800-810.doi: 10.23940/ijpe.20.05.p14.800810

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Knowledge-based Semantic Reasoning for Creativity

Delin Jinga, Yingchun Tianb*(), Chi Zhangc, Changchun Yanga,  and Hongji Yangd   

  1. aSchool of Information Science and Engineering, Changzhou University, Changzhou, 213164, China
    bAliyun School of Big Data, Changzhou University, Changzhou, 213164, China
    cCollaborative Innovation Center of eTourism, Tourism College, Beijing Union University, Beijing, 100101, China
    dSchool of Informatics, Leicester University, Leicester, LE1 7RH, UK
  • Submitted on ; Revised on ; Accepted on
  • Contact: Yingchun Tian
  • About author:Yingchun Tian received her BSc degree from the School of Software Engineering, Northeast Normal University, China in 2007 and her MSc and PhD degrees from the School of Technology, De Montfort University, UK in 2008 and 2012, respectively. She was a research associate at Loughborough University, UK in 2012. She has been a lecturer at Changzhou University since 2017. Her research interests include knowledge representation and reasoning, software engineering, and system-of-systems.
    Chi Zhang received his BSc degree in engineering mechanics from Beijing Institute of Technology, China in 2001 and his MSc degree in probability theory and mathematical statics from Beijing Institute of Technology in 2006. He is a PhD candidate in creative computing at Bath Spa University. He has been a faculty member at Beijing Institute of Technology since 2001 and Beijing Union University, China since 2006. His research interests include eTourism and tourism economics.
    Professor Changchun Yang received his BSc degree in automation from Nanjing Tech University, China in 1986 and his MSc degree in automation from East China University of Science and Technology, China in 1999. He has been a faculty member at Changzhou University since 1986. Currently, he is a professor in the School of Information Science and Engineering, Changzhou University, China. His research interests include database system applications, data mining, and big data analysis.
    Professor Hongji Yang received his BSc and MSc degrees in computer science from Jilin University, China in 1982 and 1985, respectively, and his PhD degree in computer science from Durham University, UK in 1994. He was a faculty member at Jilin University, China in 1985, at De Montfort University, UK in 1993, and at Bath Spa University, UK in 2013. Currently, Dr. Yang is a professor in the School of Informatics at Leicester University, UK. He has published over 400 refereed journal and conference papers. His research interests include software engineering, creative computing, and web and distributed computing. He has been an IEEE Computer Society Golden Core member since 2010. He is also the editor in chief of International Journal of Creative Computing.


Creativity can be challenging in the idea generation process as it is hard to formalise and control. However, there are requirements for creative ideas in many fields. Generating new and inspirational ideas is mainly manual work, and it usually happens in the individual human mind or a group of persons. There is a lack of software systems to generate creative ideas automatically. In this paper, a prototype software system based on a semantic reasoning method is proposed for assisting creativity in the general idea generation process. The kernel algorithm of the system is a set of inference rules designed on the basis of semantic computing technologies and creativity techniques, which is the core of the semantic reasoning. The fundamental information supporting the inference are domains knowledge managed as ontology bases. Furthermore, a major recommender is designed and implemented by employing the proposed idea creation method to enhance the inspiration level of university choice for teenagers. As a prototype software system, the developed major recommender application proves the feasibility and innovation of the proposed method.

Key words: idea creation, software system, ontology base, inference rules, creative computing