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Rode, H. and Hiemstra, D.
(2005)
Conceptual Language Models for Context-Aware Text Retrieval.
In: Proceedings of the 13th Text REtrieval Conference Proceedings (TREC), 16-19 Nov 2004.
.
NIST Special Publications SP 500-261.
National Institute of Standards and Technology (NIST).
ISBN not assigned
Full text available as: Official URL: http://trec.nist.gov/pubs/trec13/t13_proceedings.html  AbstractWhile participating in the HARD track our first
question was, what an IR-application should look
like that takes into account preference meta-data
from the user, without the need of explicit (manual)
meta-data tagging of the collection. Especially,
we touch the question how contextual information
can be described in an abstract model
appropriate for the IR-task, which further allows
improving and fine-tuning of the context representations
by learning from the user. As a first result,
we roughly sketch a system architecture and context
representation based on statistical language
models that fits well to the task of the HARD
track. Furthermore, we discuss issues of ranking
and score normalizations on this background. | Item Type: | Conference or Workshop Paper (Full Paper, Talk) |
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| Research Group: | EWI-DB: Databases |
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| Research Program: | CTIT-NICE: Natural Interaction in Computer-mediated Environments |
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| Research Project: | MultimediaN/N5: Semantic access |
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| Additional Information: | Imported from EWI/DB PMS [db-utwente:inpr:0000003641] |
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| ID Code: | 7326 |
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| Status: | Published |
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| Deposited On: | 28 November 2006 |
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| Refereed: | Yes |
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| International: | Yes |
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| More Information: | statisticsmetis |
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