An Ontology-Based System for Generating Mathematical Test Papers

  • Jianfeng DuEmail author
  • Xuzhi Zhou
  • Can Lin
  • Deqian Liu
  • Jiayi Cheng
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 480)


Automatic test paper generation is highly helpful in teaching and learning. In order to generate a test paper that covers as many knowledge points as possible, it is needed to discover knowledge points from exam questions. However, the problem of automatically finding knowledge points is seldom investigated in existing work. To fill this gap, this paper proposes an ontology-based method to discover knowledge points from mathematical exam questions. Accordingly, a system for automatically generating mathematical test papers is also proposed. It composes a test paper by solving a pseudo-Boolean optimization problem. Its practicality is demonstrated by a task of generating mathematical test papers from hundreds of postgraduate entrance exam questions.


Test Paper Generation Exam Questions Knowledge Points Postgraduate Entrance Exam PBO Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is partly supported by the NSFC grants (61375056 and 61005043), the Guangdong Natural Science Foundation (S2013010012928), the Undergraduate Innovative Experiment Projects in Guangdong University of Foreign Studies (1184613038 and 201411846043), and the Business Intelligence Key Team of Guangdong University of Foreign Studies (TD1202).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Jianfeng Du
    • 1
    Email author
  • Xuzhi Zhou
    • 1
  • Can Lin
    • 1
  • Deqian Liu
    • 1
  • Jiayi Cheng
    • 1
  1. 1.Guangdong University of Foreign StudiesGuangzhouChina

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