Text Categorization for Aligning Educational Standards

Author

Yilmazel, Ozgur ; Balasubramanian, Niranjan ; Harwell, Sarah C. ; Bailey, Jennifer ; Diekema, Anne R. ; Liddy, Elizabeth D.

Author_Institution

Center for Natural Language Process., Syracuse Univ., NY

fYear

2007

fDate

Jan. 2007

Firstpage

73

Lastpage

73

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

Keywords

educational administrative data processing; learning (artificial intelligence); natural language processing; standards; text analysis; vocabulary; educational standard alignment; machine learning; natural language processing; text categorization; vocabulary; Atmosphere; Earth; Natural language processing; Software libraries; Soil; Solids; Standards development; Standards organizations; Text categorization; Water resources;

fLanguage

English

Publisher

ieee

Conference_Titel

System Sciences, 2007. HICSS 2007. 40th Annual Hawaii International Conference on

Conference_Location

Waikoloa, HI

ISSN

1530-1605

Electronic_ISBN

1530-1605

Type

conf

DOI

10.1109/HICSS.2007.517

Filename

4076517