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 Opportunities: Scholarships in Brazil - Master
• Start date: June 01, 2015
• End date: July 31, 2016
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Robson Leonardo Ferreira Cordeiro
• Grantee: André dos Santos Gonzaga
• Host 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)

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. (18/05714-5, 15/05607-6, 14/21483-2)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

GONZAGA, André dos Santos. 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.