Title :
An Autogenerating Test Paper Method Based on Latent Semantic Analysis and Genetic Algorithm
Author :
Gao Huming ; Li Yanjie
Author_Institution :
Inf. Manage. Dept, Tianjin Univ. of Econ. & Finance, Tianjin
Abstract :
It is a multi-objective optimization problem to autogenerate a test paper from test bank. In this paper an autogenerating test paper method based on latent semantic analysis and genetic algorithm is proposed. Firstly the relationships of keywords among test items in a test bank are analyzed with LSA, and the weights of the test items are calculated. Then using the Genetic Algorithm to compose the test paper accorded to the weights. The proposed method can effectively select test items from Chinese test bank to compose a test paper.
Keywords :
computer aided instruction; genetic algorithms; autogenerating test paper method; genetic algorithm; latent semantic analysis; multiobjective optimization problem; Algorithm design and analysis; Education; Finance; Genetic algorithms; Information analysis; Information management; Matrix decomposition; Optimization methods; Singular value decomposition; Testing;
Conference_Titel :
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3893-8
Electronic_ISBN :
978-1-4244-3894-5
DOI :
10.1109/IWISA.2009.5072709