FUZZY COMMON SEQUENTIAL RULES MINING IN QUANTITATIVE SEQUENCE DATABASES

Abstract

Common Sequential Rules present a relationship between unordered itemsets in which the items in antecedents have to appear before ones in consequents. The algorithms proposed to find the such rules so far are only applied for transactional sequence databases, not applied for quantitative sequence databases.The goal of this paper is to propose a new algorithm for finding the fuzzy common sequential (FCS for short) rules in quantitative sequence databases. The proposed algorithm is improved by basing on the ERMiner algorithm. It is considered to be the most effective today compared to other algorithms for finding common sequential rules in transactional sequence database. FCS rules are more general than classical fuzzy sequential rules and are useful in marketing, market analysis, medical diagnosis and treatment