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The Similarity-aware Relational Division Database Operator

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André dos Santos Gonzaga
Total Authors: 1
Document type: Master's Dissertation
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB)
Defense date:
Examining board members:
Robson Leonardo Ferreira Cordeiro; Renato Bueno; Mirella Moura Moro; Caetano Traina Junior
Advisor: Robson Leonardo Ferreira Cordeiro

In Relational Algebra, the operator Division (÷) is an intuitive tool used to write queries with the concept of for all, and thus, it is constantly required in real applications. However, as we demonstrate in this MSc work, the division does not support many of the needs common to modern applications, particularly those that involve complex data analysis, such as processing images, audio, genetic data, large graphs, fingerprints, and many other non-traditional data types. The main issue is the existence of intrinsic comparisons of attribute values in the operator, which, by definition, are always performed by identity (=), despite the fact that complex data must be compared by similarity. Recent works focus on supporting similarity comparison in relational operators, but no one treats the division. MSc work proposes the new Similarity-aware Division (÷) operator. Our novel operator is naturally well suited to answer queries with an idea of candidate elements and exigencies to be performed on complex data from real applications of high-impact. For example, it is potentially useful to support agriculture, genetic analyses, digital library search, and even to help controlling the quality of manufactured products and identifying new clients in industry. We validate our proposal by studying the first two of these applications. (AU)

FAPESP's process: 15/05607-6 - Relational division by similarity in databases: formal definition, incorporation to the relational Algebra and development of algorithms with one case study in Agriculture
Grantee:André dos Santos Gonzaga
Support type: Scholarships in Brazil - Master