Automatic Spelling Corrector to improve Unified Registry analysis for Brazilian social development Adjustment of automatic spelling corrector system applied in Brazilian low-income family´s data

Abstract

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceThis dissertation has the goal to develop a solution to correct spelling errors when inserting the neighborhoods of Brazilian low-income families. The Brazil Government uses data from the Unified Registry (Cadastro Único) to diagnose the basic social right of low-income families and to map public policies based on the real needs of Brazilian society. Therefore, the best solution found was an adjustment of the string correction method, Automatic Spelling Correction (ASC) system, and an automatic dictionary creator, to the CECAD registry family status data and correction of the neighborhood names wrongly typed. The research will describe the algorithm’s process with an explanation of the main mathematical concepts