Tech Reports
Tech Report kmi-02-06 Abstract
A Spreading Activation Framework for Ontology-enhanced Adaptive Information Access
Techreport ID: kmi-02-06
Date: 2002
Author(s): Md Maruf Hasan, Motta, E., Domingue, J.B., Buckingham-Shum, S., Vargas-Vera, M. and Lanzoni, M.
This research investigates a unique Indexing Structure and Navigational Interface which make use of (1) ontology-driven knowledge (2) statistically derived indexing parameters, and (3) experts' feedback into a single Spreading Activation Framework to harness knowledge from heterogeneous knowledge assets within an organisation. Organisational ontologies capture precise knowledge about organisational entities: people, projects, activities, information sources and so on. We extract useful entities and their relationships from an ontology-driven knowledge base. We also process collections of documents (archives) accumulated in heterogeneous information-bases within an organisation and derive indexing parameters. Such information is then mapped to a weighted graph (network). The network contains three sets of nodes consists of documents, ontological entities and statistically derived entities. Document nodes are connected to both ontology-driven entities and statistically derived entities, and vice-versa with relevant weights. Retrieval is performed by spreading query-based activation into the network and selecting the most-activated nodes. Experts in the organisation either navigate the network using associative relations among nodes or with specific queries. Expert’s feedback is captured and the network weights are continuously adapted. This framework essentially combines precise knowledge (ontology-driven), non-precise knowledge (statistically driven) and Expert’s feedback (adaptation) into a single framework for adaptive information retrieval and navigation.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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