Método de reglas de asociación para el análisis de afinidad entre objetos de tipo texto
Abstract
Data mining is considered a tool to extract knowledge in large volumes of information. One of the analyzes performed in data mining is the association rules, whose purpose is to look for co-occurrences among the records of a set of data. Its main application is in the analysis of market basket, where criteria for decision making are established based on the buying behavior of customers. Some of the algorithms are A priori, Frequent Parent Growth, QFP Algorithm, CBA, CMAR, CPAR. These algorithms have been designed to analyze structured databases; At present, various applications require the processing of unstructured data known as text type Objects. The purpose of this research is to generate a method to establish the relationship between the elements that make up an object of text type, for the acquisition of relevant information from the analysis of massive data sources of the same type.
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