Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10368486 | Computer Speech & Language | 2014 | 25 Pages |
Abstract
Most research in the automatic assessment of free text answers written by students address English language. This paper handles the assessment task in Arabic language. This research focuses on applying multiple similarity measures separately and in combination. Many aspects are introduced that depend on translation to overcome the lack of text processing resources in Arabic, such as extracting model answers automatically from an already built database and applying K-means clustering to scale the obtained similarity values. Additionally, this research presents the first benchmark Arabic data set that contains 610 students' short answers together with their English translations.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Wael Hassan Gomaa, Aly Aly Fahmy,