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

Alexey An, Bakytkan Dauletbakov, Eugene Levner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 15th International Conference, CICLing 2014, Proceedings
PublisherSpringer Verlag
Pages404-416
Number of pages13
EditionPART 2
ISBN (Print)9783642549021
DOIs
StatePublished - 2014
Externally publishedYes
Event15th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2014 - Kathmandu, Nepal
Duration: 6 Apr 201412 Apr 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8404 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2014
Country/TerritoryNepal
CityKathmandu
Period6/04/1412/04/14

Keywords

  • Borda ranking method
  • Text classification
  • educational innovation projects
  • numerical classifiers

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