Automated essay content analysis based on Concept Indexing with Fuzzy C-means clustering

Author

Razon, Abigail R. ; Vargas, Ma Lourdes J ; Guevara, Rowena Cristina L ; Naval, Prospero C., Jr.

Author_Institution

Dept. of Comput. Sci., Univ. of the Philippines, Quezon City, Philippines

fYear

2010

fDate

6-9 Dec. 2010

Firstpage

1167

Lastpage

1170

Abstract

We present a new approach to essay content analysis using the dimensionality reduction algorithm called Concept Indexing (CI). Experiments were conducted to compare the performance of CI K-means and CI Fuzzy C-means with Latent Semantic Indexing (LSI). Both versions of CI outperform LSI in Exact Agreement Accuracy and Pearson´s Product-Moment Correlation Coefficient measures on sample essays taken from high school English classes.

Keywords

educational administrative data processing; indexing; natural language processing; pattern clustering; CI K-means; CI fuzzy c-means; Pearson product-moment correlation coefficient; automated essay content analysis; automated essay grading; concept indexing; dimensionality reduction algorithm; educational reinforcement tool; exact agreement accuracy; fuzzy c-means clustering; language learning; latent semantic indexing; Accuracy; Indexing; Large scale integration; Matrix decomposition; Measurement; Semantics; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems (APCCAS), 2010 IEEE Asia Pacific Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-7454-7

Type

conf

DOI

10.1109/APCCAS.2010.5775058

Filename

5775058