New algorithms for composite retrieval

Internet users constantly make searches to find objects or results of their interest, generally through terms or phrases. Traditional search offers only solutions that take into account just the individual characteristics of the results, and not the relations they have with the rest of the universe....

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Detalles Bibliográficos
Autores principales:	Feuerstein, E., Knebel, J.A., Mendez-Diaz, I., Stein, A., Zabala, P., Accenture; CONICYT; et al.; NIC Chile; RyC Consultores Asociados; Telefonica I+D
Formato:	CONF
Materias:	Composite retrieval Heuristics Computer programming Computer science Individual characteristics Internet users Search criterion Similarity criteria Heuristic algorithms
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_97815090_v_n_p_Feuerstein
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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spelling	todo:paper_97815090_v_n_p_Feuerstein2023-10-03T16:43:48Z New algorithms for composite retrieval Feuerstein, E. Knebel, J.A. Mendez-Diaz, I. Stein, A. Zabala, P. Accenture; CONICYT; et al.; NIC Chile; RyC Consultores Asociados; Telefonica I+D Composite retrieval Heuristics Computer programming Computer science Heuristics Individual characteristics Internet users Search criterion Similarity criteria Heuristic algorithms Internet users constantly make searches to find objects or results of their interest, generally through terms or phrases. Traditional search offers only solutions that take into account just the individual characteristics of the results, and not the relations they have with the rest of the universe. Typically, we are given an ordered list of the results related to the search criterion, which implies the need of changing several times the terms of the query to get to a solution that is more adequate to the intended search goal. As a solution to this problem, Composite Retrieval proposes that the results to a query may be grouped in sets of items (bundles), related through some similarity criterion, but at the same time are complementary. In this work we propose heuristic algorithms for Composite Retrieval which are evaluated experimentally, showing performance improvements over the previous results presented in the literature. © 2016 IEEE. Fil:Mendez-Diaz, I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Zabala, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_97815090_v_n_p_Feuerstein
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Composite retrieval Heuristics Computer programming Computer science Heuristics Individual characteristics Internet users Search criterion Similarity criteria Heuristic algorithms
spellingShingle	Composite retrieval Heuristics Computer programming Computer science Heuristics Individual characteristics Internet users Search criterion Similarity criteria Heuristic algorithms Feuerstein, E. Knebel, J.A. Mendez-Diaz, I. Stein, A. Zabala, P. Accenture; CONICYT; et al.; NIC Chile; RyC Consultores Asociados; Telefonica I+D New algorithms for composite retrieval
topic_facet	Composite retrieval Heuristics Computer programming Computer science Heuristics Individual characteristics Internet users Search criterion Similarity criteria Heuristic algorithms
description	Internet users constantly make searches to find objects or results of their interest, generally through terms or phrases. Traditional search offers only solutions that take into account just the individual characteristics of the results, and not the relations they have with the rest of the universe. Typically, we are given an ordered list of the results related to the search criterion, which implies the need of changing several times the terms of the query to get to a solution that is more adequate to the intended search goal. As a solution to this problem, Composite Retrieval proposes that the results to a query may be grouped in sets of items (bundles), related through some similarity criterion, but at the same time are complementary. In this work we propose heuristic algorithms for Composite Retrieval which are evaluated experimentally, showing performance improvements over the previous results presented in the literature. © 2016 IEEE.
format	CONF
author	Feuerstein, E. Knebel, J.A. Mendez-Diaz, I. Stein, A. Zabala, P. Accenture; CONICYT; et al.; NIC Chile; RyC Consultores Asociados; Telefonica I+D
author_facet	Feuerstein, E. Knebel, J.A. Mendez-Diaz, I. Stein, A. Zabala, P. Accenture; CONICYT; et al.; NIC Chile; RyC Consultores Asociados; Telefonica I+D
author_sort	Feuerstein, E.
title	New algorithms for composite retrieval
title_short	New algorithms for composite retrieval
title_full	New algorithms for composite retrieval
title_fullStr	New algorithms for composite retrieval
title_full_unstemmed	New algorithms for composite retrieval
title_sort	new algorithms for composite retrieval
url	http://hdl.handle.net/20.500.12110/paper_97815090_v_n_p_Feuerstein
work_keys_str_mv	AT feuersteine newalgorithmsforcompositeretrieval AT knebelja newalgorithmsforcompositeretrieval AT mendezdiazi newalgorithmsforcompositeretrieval AT steina newalgorithmsforcompositeretrieval AT zabalap newalgorithmsforcompositeretrieval AT accentureconicytetalnicchilerycconsultoresasociadostelefonicaid newalgorithmsforcompositeretrieval
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New algorithms for composite retrieval

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