A Practical Ontology Query Expansion Algorithm for Semantic-Aware Learning Objects Retrieval

Autor/inn/en	Lee, Ming-Che; Tsai, Kun Hua; Wang, Tzone I.
Titel	A Practical Ontology Query Expansion Algorithm for Semantic-Aware Learning Objects Retrieval
Quelle	In: Computers & Education, 50 (2008) 4, S.1240-1257 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0360-1315
DOI	10.1016/j.compedu.2006.12.007
Schlagwörter	Internet; Web Sites; Distance Education; Educational Resources; Semantics; International Organizations; Metadata; Mathematics; Information Retrieval; Cognitive Ability; Written Language + Suchen Sie Ihr Suchwort? Web-Design; Distance study; Distance learning; Fernunterricht; Bildungsmittel; Semantik; International organisation; International organisations; International organization; Internationale Organisation; Metadaten; Mathematik; Denkfähigkeit; Geschriebene Sprache
Abstract	Following the rapid development of Internet, particularly web page interaction technology, distant e-learning has become increasingly realistic and popular. To solve the problems associated with sharing and reusing teaching materials in different e-learning systems, several standard formats, including SCORM, IMS, LOM, and AICC, etc., recently have been proposed by several different international organizations. SCORM LOM, namely learning object metadata, facilitates the indexing and searching of learning objects in a learning object repository through extended sharing and searching features. However, LOM suffers a weakness in terms of semantic-awareness capability. Most information retrieval systems assume that users have cognitive ability regarding their needs. However, in e-learning systems, users may have no idea of what they are looking for and the learning object metadata. This study presents an ontological approach for semantic-aware learning object retrieval. This approach has two significant novel features: a fully automatic ontology-based query expansion algorithm for inferring and aggregating user intention based on their original short query, and another "ambiguity removal" procedure for correcting inappropriate user query terms. This approach is sufficiently generic to be embedded to other LOM-based search mechanisms for semantic-aware learning object retrieval. Focused on digital learning material and contrasted to other traditional keyword-based search technologies, the proposed approach has experimentally demonstrated significantly improved retrieval precision and recall rate. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10