Multi-attribute classification of text documents as a tool for ranking and categorization of educational innovation projects

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. © 2014 Springer-Verlag Berlin Heidelberg.