DocumentCode :
1615658
Title :
An improvement on intelligent scoring algorithm of subjective questions based on fuzzy theory
Author :
Xiaoli San ; Xiaohui San
Author_Institution :
Coll. of Inf. Sci. & Technol., Bohai Univ., Jinzhou, China
fYear :
2013
Firstpage :
847
Lastpage :
852
Abstract :
In this paper, I provide an improvement on intelligent scoring algorithm, which rely on match of key words and semantic proximity in fuzzy theory, through analyzing the habits of mind that scoring subjective questions by manually and studying current algorithms. It gives a more efficient method to scoring subjective questions and improves conventional algorithm. The main subject of this paper includes subjective questions(short answer and explain the glossary) and semi-subjective questions(completion).
Keywords :
artificial intelligence; computer aided instruction; fuzzy set theory; fuzzy theory; intelligent scoring algorithm; keywords matching; semantic proximity; semisubjective questions; subjective questions; Algorithm design and analysis; Computers; Educational institutions; Manuals; Semantics; Sensitivity; Standards; fuzzy theory; intelligent scoring; semantic proximity; subjective questions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
Type :
conf
DOI :
10.1109/CAC.2013.6775851
Filename :
6775851
Link To Document :
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