Title: A technique for semantic annotation and retrieval of e-learning objects

Authors: A. Balavivekanandhan

Addresses: Department of Media Sciences, Anna University, Chennai, India

Abstract: The primary objective of my research is to design and develop semantic annotation and retrieval model for e-learning document. In training phase, the documents from different domains are taken and the informative words from each document are obtained based on balanced mutual information and frequency of contents in each document. We then use the informative words to identify the superordinates and the objects. The superordinates, the informative words and the objects from each document will give the relation and properties of each document. The relation and properties of each document are then used to cluster the documents. In the testing phase, we give a query or a document as input to the system to retrieve the relevant documents. If a document is given as input, the relation and properties of that document are first identified and it is used to retrieve the relevant documents.

Keywords: e-learning; document clustering; balanced mutual information; one-way matching; cluster-based matching.

DOI: 10.1504/IJBIDM.2020.108035

International Journal of Business Intelligence and Data Mining, 2020 Vol.17 No.1, pp.12 - 31

Received: 26 May 2017
Accepted: 08 Dec 2017

Published online: 05 Apr 2020 *

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