Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Querying on large and complex databases by content: Challenges on variety and veracity regarding real applications

Texto completo
Autor(es):
Traina, Agma J. M. [1] ; Brinis, Safia [1] ; Pedrosa, V, Glauco ; Avaihais, Letricia P. S. [1] ; Traina Jr, Caetano
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Math & Comp Sci, Comp Sci Dept, Sao Carlos, SP - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: INFORMATION SYSTEMS; v. 86, p. 10-27, DEC 2019.
Citações Web of Science: 0
Resumo

The amount and variety of digital data currently being generated, stored and analyzed, including images, videos, and time series, have brought challenges to data administrators, analysts and developers, who struggle to comply with the expectations of both data owners and end users. The majority of the applications demand searching complex data by taking advantage of queries that analyze different aspects of the data, and need the answers in a timely manner. Content-based similarity retrieval techniques are well-suited to handle large databases, because they enable performing queries and analyses using features automatically extracted from the data, without users' intervention. In this paper, we review and discuss the challenges posed to the database and related communities in order to provide techniques and tools that can meet the variety and veracity characteristics of big and complex data, while also considering the aspects of semantical preservation and completeness of the data. Examples and results obtained over a two-decade-long experience with real applications are presented and discussed. (C) 2019 Elsevier Ltd. All rights reserved. (AU)

Processo FAPESP: 16/17078-0 - Mineração, indexação e visualização de Big Data no contexto de sistemas de apoio à decisão clínica (MIVisBD)
Beneficiário:Agma Juci Machado Traina
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 13/27101-1 - Uma abordagem para segmentação semântica explorando a multimodalidade e temporalidade de características de vídeos digitais
Beneficiário:Letrícia Pereira Soares Avalhais
Linha de fomento: Bolsas no Brasil - Doutorado