Abstract—This paper highlights semantic web techniques
and proposes architecture for e-Learning-based systems for
the academic portal. Text mining is used with the proposed
model for better processing of unstructured data available in
XML and RDF formats. An algorithm will be used to support
building a web retrieval system to extract the hidden
knowledge for the semantic web by ontologies for e-learning
items to classify and find the relationships between the leaning
items via the academic portal.
Index Terms—Semantic web, text mining, data mining, elearning, web, web architecture.
Hamad Ibrahim Alomran is with the Department of Information Management College of Computer and Information Sciences Al-Imam Muhammad Ibn Saud Islamic University, Riyadh (e-mail: email@example.com).
Cite: Hamad Ibrahim Alomran, "Text Mining-Based Semantic Web Architecture (TMSWA) for e-Learning Systems," International Journal of Machine Learning and Computing vol.4, no. 4, pp. 333-338, 2014.