Mining of Frequent and High Utility Fuzzy Sequential Patterns

Sequential pattern mining is one of the very popular data mining techniques to find patterns from databases. The variation in technique is based on the threshold used for mining which can be frequency, utility, or both. The use of fuzzy theory helps to provide natural representation by expressing parameters in linguistic terms. This paper proposes a hybrid fuzzy sequential pattern mining algorithm that expresses quantity in linguistic terms. The proposed method generates less number of patterns than the existing algorithms, according to the results of the experiments.