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An extensible framework for automatic knowledge extraction from student blogs

Connor, AM; Martin, M; Joe, S
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AIRCC_IJITE_Connor_Extensible Framework_Final.pdf (142.3Kb)
Permanent link
http://hdl.handle.net/10292/7539
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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
Date
June 19, 2014
Source
International Journal on Integrating Technology in Education, vol.3(2), pp.9 - 18
Item Type
Journal Article
Publisher
AIRCC Publishing Corporation
DOI
10.5121/ijite.2014.3202
Publisher's Version
http://airccse.org/journal/ijite/current2014.html
Rights Statement
AIRCC Publishing Corporation is an emerging peer-reviewed, academic open access publisher which strictly focuses in all areas of Computer Science and Engineering.

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