Document Type
Conference Paper
Journal/Book Title/Conference
Hawaii International Conference on System Sciences
Publication Date
2007
First Page
73b
Last Page
73b
Abstract
Standard alignment (where standards describing similar concepts are correlated) is a necessary task in providing full access to educational resources. Manual alignment is time consuming and expensive. We propose an automatic alignment system, using machine learning techniques utilizing natural language processing. In this paper we discuss our experiments on text categorization for automatic alignment. We explore the role of relevant vocabulary sets in automatic alignment.
Recommended Citation
Yilmazel, O., Balasubramanian, N., Harwell, S. C., Bailey, J., Diekema, A. R., & Liddy, E. D. (2007). Text Categorization for Aligning Educational Standards. Hawaii International Conference on System Sciences, Waikoloa, Hawaii, January 3-6, 2007.
Included in
Educational Assessment, Evaluation, and Research Commons, Instructional Media Design Commons
Comments
Originally published by the Institute of Electrical and Electronics Engineers. Available online through the Hawaii International Conference on System Sciences.