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 &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...
We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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