Topic model methods for automatically identifying out-of-scope resources
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Aspects of 'relevance' in the alignment of curriculum with educational standards
Information Processing and Management: an International Journal
Text categorization for assessing multiple documents integration, or John Henry visits a data mine
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Journal of the American Society for Information Science and Technology
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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.