Information Retrieval and Language Model based Expert Search
This event took place on Wednesday 24 January 2007 at 11:30
Jianhan Zhu
Both research and industry communities are paying lots of attention to expert search recently. Text REtrieval Conference (TREC) has organized expert search task for 2005 and 2006. We have participated in TREC 2006 expert search task and achieved the best run judged by all information retrieval measures among 23 groups. We propose to integrate three document characteristics, namely, document authority, document internal structure, and various levels of associations between an expert and a search topic, in addition to document content, in a two-stage language model for effective expert search. We have used the TREC W3C dataset to test the effectiveness of the three document characteristics in terms of measures such as mean average precision, bpref, and Precision@10 etc.
This event took place on Wednesday 24 January 2007 at 11:30
Both research and industry communities are paying lots of attention to expert search recently. Text REtrieval Conference (TREC) has organized expert search task for 2005 and 2006. We have participated in TREC 2006 expert search task and achieved the best run judged by all information retrieval measures among 23 groups. We propose to integrate three document characteristics, namely, document authority, document internal structure, and various levels of associations between an expert and a search topic, in addition to document content, in a two-stage language model for effective expert search. We have used the TREC W3C dataset to test the effectiveness of the three document characteristics in terms of measures such as mean average precision, bpref, and Precision@10 etc.
Future Internet
KnowledgeManagementMultimedia &
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HypermediaNew Media SystemsSemantic Web &
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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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