Conceptual Language Models for Context-Aware Text Retrieval

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Conceptual Language Models for Context-Aware Text Retrieval
While 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 inn 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. Keywords Contextual Information Retrieval, Context Modeling, Language Models
Henning Rode, Djoerd Hiemstra
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where TREC
Authors Henning Rode, Djoerd Hiemstra
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