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Multi-attribute Classification of Text Documents as a Tool for Ranking and Categorization of Educational Innovation Projects

  • Alexey An
  • Bakytkan Dauletbakov
  • Eugene Levner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8404)

Abstract

We suggest a semi-automatic text processing method for ranking and categorization of educational innovation projects (EIP). The EIP is a nation-wide program for strategic development of an university or a group of academic institutions. Our approach to the EIP evaluation is based on the multi-dimensional system ranking that uses quantitative indicators for three main missions of higher education institutions, namely, education, research, and knowledge transfer. The main part of this paper is devoted to the design of a semi-automatic method for ranking the EIPs exploiting multi-attribute document classification. The ranking methodology is based on the generalized Borda voting method.

Keywords

Text classification numerical classifiers Borda ranking method educational innovation projects 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Alexey An
    • 1
  • Bakytkan Dauletbakov
    • 1
  • Eugene Levner
    • 2
  1. 1.The Al-Farabi Kazakh National UniversityAlmatyRepublic of Kazakhstan
  2. 2.Ashkelon Academic ColegeAshkelon, and Holon Institute of TechnologyHolonIsrael

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