Automatic metadata generation & evaluation

Elizabeth D. Liddy, Eileen Allen, Sarah Harwell, Susan Corieri, Ozgur Yilmazel, N. Ercan Ozgencil, Anne Diekema, Nancy McCracken, Joanne Silverstein, Stuart Sutton

Research output: Contribution to journalConference articlepeer-review

30 Scopus citations

Abstract

The poster reports on a project in which we are investigating methods for breaking the human metadata-generation bottleneck that plagues Digital Libraries. The research question is whether metadata elements and values can be automatically generated from the content of educational resources, and correctly assigned to mathematics and science educational materials. Natural Language Processing and Machine Learning techniques were implemented to automatically generate metadata for learning resources provided by the Gateway for Education (GEM), a service that offers web access to a wide range of educational materials. In a user study, education professionals evaluated the metadata assigned to learning resources by either automatic tagging or manual assignment. Results show minimal difference in the eyes of the evaluators between automatically generated metadata and manually assigned metadata.

Original languageEnglish (US)
Pages (from-to)401-402
Number of pages2
JournalSIGIR Forum (ACM Special Interest Group on Information Retrieval)
StatePublished - Dec 1 2002
EventProceedings of the Twenty-Fifth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - Tampere, Finland
Duration: Aug 11 2002Aug 15 2002

Keywords

  • Metadata generation
  • NLP

ASJC Scopus subject areas

  • Management Information Systems
  • Hardware and Architecture

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