LOMGen
The Learning Object Metadata Generator (LOMGen) facilitates semi-automatic generation of Learning Object Metadata by parsing HTML files to extract keywords and keyphrases. It identifies related terms not explicitly present in the Learning Object, enhancing metadata richness. LOMGen functions as an AgentMatcher for indexing Learning Objects and allows efficient querying based on generated keywords and keyphrases. This tool incorporates extended parsing techniques, Part-of-Speech tagging, and a WordNet interface for comprehensive text analysis.
LOMGen
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Presentation Transcript
Learning Object Repository (LOR) CANLOM Metadata Repository HTML file Validated XML file HTML Parser Updated XML file CANLOM XML file template Frequency Counter Synonym & Related Terms Finder XML Generator Keywords & Keyphrases Database LOMGen Learning Object Metadata Generator Features Architecture • Semi-automatic metadata generation, • applied to Learning Object Metadata • Shallow parsing of HTML objects to extract • keywords/keyphrases • Finds related terms and phrases, which are • not explicit in the Learning Object • LOMGen acts as an AgentMatcher • component for indexing Learning Objects • and for querying with keywords/keyphrases Retrieved HTML file from LOR Metadata Administrator Fills in remaining tag values Uses template, updates general identifier Retrieve Update Extracted keyphrases, description and title • Current work • Extended parsing to derive weighted metadata & queries • Part-of-Speech Tagging • WordNet interface for text analysis Researchers Dr. Virendra C. Bhavsar Dr. Harold Boley Anurag Singh Faculty of Computer Science, University of New Brunswick, P.O. Box 4400, 540 Windsor Street, Gillin Hall E126, Fredericton, NB E3B 5A3 Phone: (506) 453-4566 Fax: (506) 453-3566 Email: fcs@unb.ca June 16, 2004