Tech Reports
Tech Report kmi-04-04 Abstract
Semantic Learning Webs
Techreport ID: kmi-04-04
Date: 2004
Author(s): Arthur Stutt, Enrico Motta
If current research is successful there will be a plethora of e-learning platforms making use of a varied menu of reusable educational material or learning objects. For the learner, the semanticized Web will, in addition, offer rich seams of diverse learning resources over and above the course materials (or learning objects) specified by course designers. This much is already in development. But we can go much further. Semantic technologies make it possible not only to reason about the Web as if it is one extended knowledge base but also to provide a range of additional educational semantic web services such as summarization, interpretation or sense-making, structure-visualization, and support for argumentation. It can thus provide the means for learners to navigate through the plethora of sources, find help in their interpretation of material by contextualizing it to debates and narratives, and actively enter into these debates or construct these stories as members of living online communities of learners. In this paper we present a model of how the Semantic web could be used for learning. In particular we discuss Knowledge Navigation which is the process of linking from web document to web document by means of Knowledge Charts. These are a new form of learning object which represent contextualized community knowledge such as the debates, narratives, and analogies which animate any field. By combining navigation with a means of learner participation within Knowledge Neighbourhoods (locations on the Web where communities collaborate to create and use representations of their knowledge ) the learner becomes, not a passive recipient of knowledge, but the sort of critical thinker able to deal with the complexity of the material available in a knowledge based society.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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