The Quest of Information Retrieval in Semantic Web
This event took place on Wednesday 13 September 2006 at 11:30
Miriam Fernández
Semantic search has been one of the motivations of the Semantic Web since it was envisioned. In my thesis I research the development of a new retrieval model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In this view of Information Retrieval on the Semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, my current approach includes an ontology-based scheme for the semiautomatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. The method has been tested on corpora of significant size, showing promising results respect to keyword-based search, and providing ground for further analysis and research.
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This event took place on Wednesday 13 September 2006 at 11:30
Miriam Fernández
Semantic search has been one of the motivations of the Semantic Web since it was envisioned. In my thesis I research the development of a new retrieval model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In this view of Information Retrieval on the Semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, my current approach includes an ontology-based scheme for the semiautomatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. The method has been tested on corpora of significant size, showing promising results respect to keyword-based search, and providing ground for further analysis and research.
Download PowerPoint presentation (87kb ZIP file)
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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.
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