Automatic Metadata Tagging of Learning Resource Types |
Author(s): |
| Tripti Malviya , Maulana Azad National Institute of Technology, Bhopal (M.P.) , India; Prof. Devshri Roy , Maulana Azad National Institute of Technology, Bhopal (M.P.) , India |
Keywords: |
| Learning Object Metadata, Learning Object Type, text classification |
Abstract |
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Metadata is data about data. IEEE learning object metadata is a standard metadata. For relevant retrieval ofa learning material, it is tagged with metadata and kept in the learning object repository. Generally metadata tagging is done manually. Manual metadata tagging is a time consuming and tedious job. To avoid this drawback, we have worked on automatic metadata tagging. We have presented an automatic way to determine a set of metadata from the IEEE LOM 5.2 i.e. the type of learning resource type.In this work, we have mainly determined the narrative text, experiment type and experiment type learning resources. We have developed different pattern bases for different type of learning resources. Pattern matching algorithms with various rules have been developed for extracting the type of learning resource type. Experimental results are shown to depict the accuracy achieved. |
Other Details |
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Paper ID: IJSRDV1I2035 Published in: Volume : 1, Issue : 2 Publication Date: 01/05/2013 Page(s): 197-200 |
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