Title: Using taxonomic indexing trees to efficiently retrieve SCORM-compliant documents in e-learning grids
Authors: Shih, Wen-Chung
Tseng, Shian-Shyong
Yang, Chao-Tung
Department of Computer Science
Keywords: e-learning;SCORM;grid computing;globus toolkit;information retrieval
Issue Date: 2008
Abstract: With the flourishing development of e-Learning, more and more SCORM-compliant teaching materials are developed by institutes and individuals in different sites. In addition, the e-Learning grid is emerging as an infrastructure to enhance traditional e-Learning systems. Therefore, information retrieval schemes supporting SCORM-compliant documents on grid environments are gaining its importance. To minimize the query processing time and content transmission time, our idea is to use a bottom-up approach to reorganize documents in these sites based on their metadata, and to manage these contents in a centralized manner. In this paper, we design an indexing structure named Taxonomic Indexing Trees (TI-trees). A TI-tree is a taxonomic structure and has two novel features: 1) reorganizing documents according to the Classification metadata such that queries by classes can be processed efficiently and 2) indexing dispersedly stored documents in a centralized manner which is suitable for common grid middleware. This approach is composed of a Construction phase and a Search phase. In the former, a local TI-tree is built from each Learning Object Repository. Then, all local TI-trees are merged into a global TI-tree. In the latter, a Grid Portal processes queries and presents results with estimated transmission time to users. Experimental results show that the proposed approach can efficiently retrieve SCORM-compliant documents with good scalability.
URI: http://hdl.handle.net/11536/14309
ISSN: 1436-4522
Volume: 11
Issue: 2
Begin Page: 206
End Page: 226
Appears in Collections:Articles