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The goal of our 18 month NSDL-funded project is to develop Natural Language Processing and Machine Learning technology which will accomplish automatic metadata generation for individual educational resources in digital collections. The metadata tags that the system will be learning to automatically assign are the full complement of Gateway to Educational Materials (GEM) metadata tags–from the nationally recognized consortium of organizations concerned with access to educational resources. The documents that comprise the sample for this research come from the Eisenhower National Clearinghouse on Science and Mathematics.

The significance of this project in terms of the Digital Library movement is that high-quality automatic assignment of metadata is essential if we are going to break the human metadata-generation bottleneck that has plagued the common goal of providing timely access to textual …