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Learning to Choose : automatic Selection of the Information Retrieval Parameters

Bigot, Anthony and Déjean, Sébastien and Mothe, Josiane Learning to Choose : automatic Selection of the Information Retrieval Parameters. (2014) In: Spanish Conference on Information Retrieval, 19 June 2014 - 20 June 2014 (Coruña, Spain). (Unpublished)

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Official URL: http://ceri2014.udc.es/

Abstract

In this paper we promote a selective information retrieval process to be applied in the context of repeated queries. The method is based on a training phase in which the meta search system learns the best parameters to use on a per query basis. The training phase uses a sample of annotated documents for which document relevance is known. When an equal-query is submitted to the system, it automatically knows which parameters it should use to treat the query. This Learning to choose method is evaluated using simulated data from TREC campaigns. We show that system performance highly increases in terms of precision (MAP), speci cally for the queries that are di cult to answer, when compared to any unique system con guration applied to all the queries.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-01118863
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:20 Feb 2015 10:08

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