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
Semantic Web and Knowledge Services is...
Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.
List all Semantic Web and Knowledge Services Projects
Check out these Hot Semantic Web and Knowledge Services Technologies:
List all Semantic Web and Knowledge Services Technologies
