Metaextract: an NLP system to automatically assign metadata

We have developed MetaExtract, a system to automatically assign Dublin Core + GEM metadata using extraction techniques from our natural language processing research. MetaExtract is comprised of three distinct processes: eQuery and HTML-based Extraction modules and a Keyword Generator module. We conducted a Web-based survey to have users evaluate each metadata element’s quality. Only two of the elements, Title and Keyword, were shown to be significantly different, with the manual quality slightly higher. The remaining elements for which we had enough data to test were shown not to be significantly different; they are: Description, Grade, Duration, Essential Resources, Pedagogy-Teaching Method, and Pedagogy-Group. Categories and Subject Descriptors H.3.7 [Digital Libraries]: Standards, System Issues, User Issues I.2.7 [Artificial Intelligence]: Natural Language Processing General Terms: Measurement, Design

• Type: Conference
• Year: 2004
• Where: JCDL
• Authors: Ozgur Yilmazel, Christina M. Finneran, Elizabeth D. Liddy
• Keywords: HTML-based Extraction Modules, JCDL 2004, Keyword Generator Module, Natural Language Processing