An Extensible Framework for Automatic Knowledge Extraction From Studen Blogs
Author(s) -
Andy M. Connor,
Matthew Martin,
Sam Joe
Publication year - 2014
Publication title -
international journal on integrating technology in education
Language(s) - English
Resource type - Journals
eISSN - 2320-3935
pISSN - 2320-1886
DOI - 10.5121/ijite.2014.3202
Subject(s) - computer science , extraction (chemistry) , world wide web , information retrieval , data science , chemistry , chromatography
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
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