Optimization of algorithm to identification of duplicate tuples through similarity phonetic based on multithreading
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Abstract
Aiming to ensure greater reliability and consistency of data stored in the database, the data cleaning stage is set early in the process of Knowledge Discovery in Databases (KDD) and is responsible for eliminating problems and adjust the data for the later stages, especially for the stage of data mining. Such problems occur in the instance level and schema, namely, missing values, null values, duplicate tuples, values outside the domain, among others. Several algorithms were developed to perform the cleaning step in databases, some of them were developed specifically to work with the phonetics of words, since a word can be written in different ways. Within this perspective, this work presents as original contribution an optimization of algorithm for the detection of duplicate tuples in databases through phonetic based on multithreading without the need for trained data, as well as an independent environment of language to be supported for this. © 2011 IEEE.
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Algorithm, Data cleansing, Duplicated tuples, Data cleaning, Knowledge discovery in database, Missing values, Multi-threading, Null value, Database systems, Linguistics, Optimization, Algorithms
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English
Citation
Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 299-304.





