| Structural relevance: a common basis for the evaluation of structured document retrieval |
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Conference on Information and Knowledge Management
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Proceeding of the 17th ACM conference on Information and knowledge management
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Napa Valley, California, USA
SESSION: IR: structured documents
table of contents
Pages 1153-1162
Year of Publication: 2008
ISBN:978-1-59593-991-3
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Authors
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M S. Ali
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University of Toronto, Toronto, ON, Canada
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Mariano P. Consens
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University of Toronto, Toronto, ON, Canada
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Gabriella Kazai
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Microsoft, London, United Kingdom
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Mounia Lalmas
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University of London, London, United Kingdom
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ABSTRACT
This paper presents a unified framework for the evaluation of a range of structured document retrieval (SDR) approaches and tasks. The framework is based on a model of tree retrieval, evaluated using a novel extension of the Structural elevance (SR) measure. The measure replaces the assumption of independence in traditional information retrieval (IR) with a notion of redundancy that takes into account the user navigation inside documents while seeking relevant information. Unlike existing metrics for SDR, our proposed framework does not require the computation of an ideal ranking which has, thus far, prevented the practical application of such measures. Instead, SR builds on a Markovian model of user navigation that can be estimated through the use of structural summaries. The results of this paper (supported by experimental validation using INEX data) show that SR defined over a tree retrieval model can provide a common basis for the evaluation of SDR approaches across various structured search tasks.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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