[01] Joshua Babatunde Agbogun, Department of Mathematical Sciences, Kogi State University, Anyigba, Nigeria. [02] Vincent Andrew Akpan, Department of Biomedical Technology, The Federal University of Technology, Akure, Nigeria.

This paper proposes a machine learning approach for information extraction of structured academic data from unstructured web documents. The current challenges of information extraction have been critically examined as well as the state-of-the-art of structured data extraction. The approach used has been simplified and presented using a comprehensive flowchart. The machine learning information extraction scheme was validated using Kogi State University (KSU), Anyigba, Kogi State-Nigeria. The preliminary studies of KSU as well as an organogram of KSU are presented in the paper. The feasibility and realization of the machine learning algorithms for information extraction of structured academic data from unstructured web documents were highlighted and the goals accomplished were also listed.

Artificial Neural Networks, Information Extraction, Machine Learning, Structured Academic Data, Unstructured Web Documents

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