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Relational division by similarity in databases: formal definition, incorporation to the relational Algebra and development of algorithms with one case study in Agriculture

Grant number: 15/05607-6
Support type:Scholarships in Brazil - Master
Effective date (Start): June 01, 2015
Effective date (End): July 31, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal researcher:Robson Leonardo Ferreira Cordeiro
Grantee:André dos Santos Gonzaga
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The relational Algebra division operator allows the representation of simple queries with the concept for everyone, and so it is constantly required for real applications. However, it is evident in this research project that the division does not meet the requirements of many current applications, especially when analyzing complex data such as images, audio, texts, fingerprinting, large graphs, among others. Analyzing the problem arises that the main limitation is the existence of comparisons intrinsic attributes to the relational division, which, by definition, are always performed by identity, as complex objects are to be compared for similarity. Today, there are proposals in the literature of relational operators supported the similarity of complex objects, however, no treats relational division. This project proposes to investigate and extend the relational Algebra division operator to better adapt it to the demands of current applications through support comparisons of values of attributes similarity. It is shown here that the division similarity is of course appropriate to answer several queries with a concept of candidate elements and requirements described in the project, involving complex data from real applications of high impact, with potential for example, to support agricultural production, search in digital libraries, quality control of production in industries, customer selection in companies, and even the identification of promising shares on stock exchanges. To validate the work, we propose a case study to support strategic decision making in agriculture, through the automatic identification of suitable municipalities for planting certain crops, based on remote sensing image analysis. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
GONZAGA, ANDRE DOS SANTOS; CORDEIRO, ROBSON L. F. The similarity-aware relational division database operator with case studies in agriculture and genetics. INFORMATION SYSTEMS, v. 82, p. 71-87, MAY 2019. Web of Science Citations: 0.
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
. The Similarity-aware Relational Division Database Operator. 2017. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.