Vol. 4 Issue 1
Year: 2016
Issue:Mar-May
Title:Mining Fuzzy Association Rules using Various Algorithms: A Survey
Author Name:O. Gireesha and O. Obulesu
Synopsis:
Data mining is the process of extracting knowledge from large databases. Different types of knowledge and technology were introduced for the data mining in the last decade. Among them, finding association rules from transactional data is a common task in day-to-day life. The majority of studies deal with how binary valued transaction data is possibly handled. In real-world applications, the transaction of data consists of quantitative and fuzzy values. So, data mining algorithms have to deal with different types of data present as a confront to researchers in this field. In this paper, the authors discussed a few of the fuzzy mining concepts and techniques, along with the algorithms correlated to association rule discovery. Some fuzzy mining techniques including mining fuzzy association rules, and the membership functions are described in this paper.
Year: 2016
Issue:Mar-May
Title:Mining Fuzzy Association Rules using Various Algorithms: A Survey
Author Name:O. Gireesha and O. Obulesu
Synopsis:
Data mining is the process of extracting knowledge from large databases. Different types of knowledge and technology were introduced for the data mining in the last decade. Among them, finding association rules from transactional data is a common task in day-to-day life. The majority of studies deal with how binary valued transaction data is possibly handled. In real-world applications, the transaction of data consists of quantitative and fuzzy values. So, data mining algorithms have to deal with different types of data present as a confront to researchers in this field. In this paper, the authors discussed a few of the fuzzy mining concepts and techniques, along with the algorithms correlated to association rule discovery. Some fuzzy mining techniques including mining fuzzy association rules, and the membership functions are described in this paper.
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