Parallel Generation of Association Rules – Use Case: Psychometric Evaluation


Mining of association rules consists of determining relations among variables in the form of rules in large databases, one of the algorithms most used to perform this task is the Apriori algorithm. This article proposes the parallelization of the Apriori algorithm applied to the Cattell’s questionnaire Sixteen Personality Factor, known as the 16PF questionnaire, to generate association rules among different questions. The use case used has a database that contains 49,150 questionnaires answered, with 163 questions per questionnaire. Results obtained show four times less execution time between the proposed parallel algorithm and the serial algorithm, in addition, the results show associations with confidence values greater than 97% (with two variables) and greater than 98% (with three variables), which it would be expected from the point of view of traditional psychology.



Keywords: rules of association, Apriori algorithm, parallelization, personality questionnaire

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