Frequent Itemset Mining is an important approach for Market Basket Analysis. Earlier, the frequent itemsets are determined based on the customer transactions of binary data. Recently, fuzzy data are used to determine the frequent itemsets because it provides the nature of frequent itemset ie. , it describes whether the frequent itemset consists of only highly purchased items or medium purchased...

Data mining methods which combine techniques from database research, statistics and artificial intelligence have been applied to many research disciplines including engineering, finance and medicine.The objective of this paper is to describe the feasibility of applying a predictive data mining technique to predict the survival of AIDS. An adaptive fuzzy regression technique, FuReA, was used to ...

Due to the increasing occurrence of very large databases, mining useful information and knowledge from transactions is evolving into an important research area. In the past, many algorithms were proposed for mining association rules, most of which were based on items with binary values. Transactions with quantitative values are, however, commonly seen in real-world applications. In this paper, ...

Data mining is most commonly used in attempts to induce association rules from transaction data. Transactions in real-world applications, however, usually consist of quantitative values. This paper thus proposes a fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions. We present a GA-based framework for finding membership funct...

Intrusion Detection is one of the important area of research. Our work has explored the possibility of integrating the fuzzy logic with Data Mining methods using Genetic Algorithms for intrusion detection. The reasons for introducing fuzzy logic is two fold, the first being the involvement of many quantitative features where there is no separation between normal operations and anomalies. Thus f...

In security infrastructure network intrusion detection system plays an important role. There are number of novels attacks in present scenario and it is not an easy to determine that. So in this paper we discuss the few new integrated network detection system. This paper also gives a better NIDS as a result because the numbers of good techniques have been integrated in this paper. So as conclude...

due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. association rules mining is one of the data mining techniques to extract useful patterns in the form of association rules. one of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. hiding the as...

Although an overall knowledge discovery process consists of a distinct pre-processing stage followed by the data mining step, it seems that existing formal concept analysis (FCA) and association rules mining (ARM) approaches, dealing with many-valued contexts, mainly focus on the data mining stage. An “intelligent” pre-processing of input contexts is often absent in existing FCA/ARM approaches,...