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dc.contributor.authorZaragoza, David
dc.contributor.authorCardinale, Yudith
dc.contributor.authorRukoz, Marta
dc.date.accessioned2017-01-09T12:00:36Z
dc.date.available2017-01-09T12:00:36Z
dc.date.issued2015
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16138
dc.language.isoenen
dc.subjectIndexing Mechanisms
dc.subjectSimilarly Search
dc.subjectQuery Strategies
dc.subject.ddc005.7en
dc.titleSimSearch: similarity search framework based on indexing techniques in metric spaces
dc.typeCommunication / Conférence
dc.contributor.editoruniversityotherUniversida Simon Bolivar
dc.description.abstractenSimilarity search in metric spaces refers to searching elements in data repositories that are similar to an element supplied by the user (query example). Similarity functions are used to determine which elements in the data repositories are similar to the query example and indexing mechanisms are used to improve the efficiency in the search. Classic indexation mechanisms such as LSH, M-Index, and M-Tree behave different according to the dimensionality in the metric space, volume of data repositories, and query strategies. In this paper, we describe SimSearch, a modular and flexible framework for similarity search in metric spaces, which allows to use, analyse, compare, and add several indexation mechanisms, search approaches, and query strategies. SimSearch allows doing queries given one or more example elements to obtain the set of elements more similar to the query examples, using query composition and Skyline. We show the variability of performance of several indexation mechanisms, including LSH-ML (our proposed variant of LSH), with experimental study in the domain of images represented by a feature vector in a high dimensionality metric space and Web Services represented by a vector with the values of Quality of Service (QoS) parameters.
dc.identifier.citationpages90-97
dc.relation.ispartoftitleMEDES '15 Proceedings of the 7th International Conference on Management of computational and collective intElligence in Digital EcoSystems
dc.relation.ispartofeditorRichard Chbeir, Yannis Manolopoulos, Victor Pellegrini Mammana, Eduardo Antonio Modena, Agma J. M. Traina, Oscar Salviano Silva Filho, Youakim Badr, Frédéric Andrès
dc.relation.ispartofpublnameACM Press
dc.relation.ispartofpublcityNew York
dc.relation.ispartofdate2015
dc.contributor.countryeditoruniversityotherVENEZUELA, BOLIVARIAN REPUBLIC OF
dc.subject.ddclabelOrganisation des donnéesen
dc.relation.ispartofisbn978-1-4503-3480-8
dc.relation.forthcomingnonen
dc.identifier.doi10.1145/2857218.2857233
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2017-01-19T17:42:35Z
hal.person.labIds25894
hal.person.labIds25894
hal.person.labIds989
hal.identifierhal-01429953*


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