A Clustering Visualization Query Language

• Ana Sodré Federal University of Paraná
• Luis Floriano Federal University of Paraná
• Aurora Pozo Federal University of Paraná
• Carmem Hara Federal University of Paraná

DOI: https://doi.org/10.5753/eniac.2020.12150

Abstract

In recent years, machine learning techniques have been used in several areas and applications. However, the application of such techniques still relies on professional experts, with ability to execute the required sequence of tasks. In the database area, SQL has democratized the use of database management systems (DBMS) for the end user through a simple declarative language, which resembles natural language. In this paper, Clustering Visualization Query Language (CVQL) is proposed, which extends SQL to execute clustering and visualization tasks. Clustering is a technique used to divide data into groups that share similar features. The visualization of these groupings in different graphical forms is an essential functionality for the end user to analyze the results. CVQL was implemented using mySQL DBMS and scikit-learn library. To present the system, we consider an 8 lines query example on a real database of Covid-19 cases in the USA. The execution of the same sequence os tasks would require 140 lines of code in Python, which shows the usefulness of CVQL.

Keywords: query language, SQL, clustering, visualization, machine learning

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