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.
