Informatika i Ee Primeneniya [Informatics and its Applications]
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Inform. Primen.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Informatika i Ee Primeneniya [Informatics and its Applications], 2013, Volume 7, Issue 1, Pages 94–104 (Mi ia249)  

This article is cited in 1 scientific paper (total in 1 paper)

Information method for assessment semantic adequacy of texts

L. A. Kuznetsov, V. F. Kuznetsova

Lipetsk State Technical University
Full-text PDF (270 kB) Citations (1)
References:
Abstract: A problem of automated knowledge examination is considered based on intelligent comparison of student's answers with reference knowledge chunks. In order to increase relevance of automatically drawn conclusions, the information theory ground is used to develop the original methodology of textual content closeness evaluation. As a part of this work, this approach is applied to evaluate how close students' essays match reference textual blocks, relating to a subject.
Keywords: semantic similarity texts; probabilistic model of text; information theory; entropy; transmitted information of texts; knowledge estimate automatization.
Document Type: Article
Language: Russian
Citation: L. A. Kuznetsov, V. F. Kuznetsova, “Information method for assessment semantic adequacy of texts”, Inform. Primen., 7:1 (2013), 94–104
Citation in format AMSBIB
\Bibitem{KuzKuz13}
\by L.~A.~Kuznetsov, V.~F.~Kuznetsova
\paper Information method for assessment semantic adequacy of~texts
\jour Inform. Primen.
\yr 2013
\vol 7
\issue 1
\pages 94--104
\mathnet{http://mi.mathnet.ru/ia249}
Linking options:
  • https://www.mathnet.ru/eng/ia249
  • https://www.mathnet.ru/eng/ia/v7/i1/p94
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Информатика и её применения
    Statistics & downloads:
    Abstract page:240
    Full-text PDF :175
    References:28
    First page:3
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024