An Extensible Framework for Automatic Knowledge Extraction From Studen Blogs
International Journal on Integrating Technology in Education (IJITE)
ISSN: 2320 - 1886(Online; 2320 - 3935(Print)
Article Title :
An Extensible Framework for Automatic Knowledge Extraction From Studen Blogs
Author Details :
Dr Andy M. Connor and Matthew Martin and Sam Joe
Auckland University of Technology, Auckland, New Zealand
ABSTRACT
This article introduces a framework for automatically extracting knowledge from student blogs and injecting it into a shared resource, namely a Wiki. This is motivated by the need to preserve knowledge generated by students beyond their time of study. The framework is described in the context of the Bachelor of Creative Technologies degree at the Auckland University of Technology in New Zealand where it is being deployed alongside an existing blogging and ePortfolio process. The framework uses an extensible, layered architecture that allows for incremental development of components in the system to enhance the functionality over time. The current implementation is in beta-testing and uses simple heuristics in the core components. This article presents a road map for extending the functionality to improve the quality of knowledge extraction by introducing techniques from the artificial intelligence field.
KEYWORDS
Blogging, Wikis, Knowledge Extraction, Enhanced Learning
Original Source URL : http://airccse.org/journal/ijite/papers/3214ijite02.pdf
For more details : http://airccse.org/journal/ijite/vol3.html
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