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Text Categorization for Aligning Educational Standards
Big Island, Hawaii January 03-January 06
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HICSS.2007.51740th Annual Hawaii International Conf ...
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Ozgur Yilmazel, Syracuse University
Niranjan Balasubramanian, Syracuse University
Sarah C. Harwell, Syracuse University
Jennifer Bailey, Syracuse University
Anne R. Diekema, Syracuse University
Elizabeth D. Liddy, Syracuse University
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.
Citation:
Ozgur Yilmazel, Niranjan Balasubramanian, Sarah C. Harwell, Jennifer Bailey, Anne R. Diekema, Elizabeth D. Liddy, "Text Categorization for Aligning Educational Standards," hicss, pp.73b, 40th Annual Hawaii International Conference on System Sciences (HICSS'07), 2007
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