KMi Seminars
Placename Disambiguation with Co-occurrence Models
This event took place on Wednesday 06 December 2006 at 11:30

 
Simon Overell Imperial College London, and KMi, The Open University

My talk will cover an introduction to Geographic Information Retrieval (GIR) and the advantages provided by indexing placenames as unambiguous locations. I will describe our GIR system which generates a large-scale co-occurrence model and applies this model to the problem of placename disambiguation. The data for the model is mined from Wikipedia and applied to the GeoCLEF corpus. An example of placename disambiguation could be when "London" is referred to in text, is it "London, UK" or "London, Ontario"? The motivation behind this problem is to make un-annotated data machine readable and allow users to query and browse data geographically. The talk will begin with a description of GIR, placename disambiguation techniques and the use of Wikipedia as a corpus. Then a description of my probabilistic models, using first and higher orders of co-occurrence. The talk will conclude with our findings on how Information Retrieval methods can be enhanced with Geographic
Knowledge.

 
KMi Seminars
KMi 2013 - A review of the year

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Journal | 25 years of knowledge acquisition
 

Semantic Web and Knowledge Services is...


Semantic Web and Knowledge Services
"The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation" (Berners-Lee et al., 2001).

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.