NDLI: Parameter sensitivity in the probabilistic model for ad-hoc retrieval

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Parameter sensitivity in the probabilistic model for ad-hoc retrieval

Content Provider	ACM Digital Library
Author	Ounis, Iadh He, Ben
Abstract	The term frequency normalisation parameter sensitivity is an important issue in the probabilistic model for Information Retrieval. A high parameter sensitivity indicates that a slight change of the parameter value may considerably affect the retrieval performance. Therefore, a weighting model with a high parameter sensitivity is not robust enough to provide a consistent retrieval performance across different collections and queries. In this paper, we suggest that the parameter sensitivity is due to the fact that the query term weights are not adequate enough to allow informative query terms to differ from non-informative ones. We show that query term reweighing, which is part of the relevance feedback process, can be successfully used to reduce the parameter sensitivity. Experiments on five Text REtrieval Conference (TREC) collections show that the parameter sensitivity does remarkably decrease when query terms are reweighed.
Starting Page	263
Ending Page	272
Page Count	10
File Format	PDF
ISBN	9781595938039
DOI	10.1145/1321440.1321479
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-11-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Relevance feedback Query term reweighing Parameter sensitivity
Content Type	Text
Resource Type	Article

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