In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to...

Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. Data mining is a computational intelligence discipline that contributes tools for data analysis, discovery of new knowledge, and autonomous decision making. Clustering is a primary data description method in data mining which group’s most similar data. The data clustering is an impor...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW) [8]. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and suppor...

Department of Computer Science & Engineering/Shriram College of Engineering & Management [SRCEM] Banmore, Gwalior (MP)/India, 474003 _______________________________________________________________________________________ Abstract: Data mining is sorting through data to identify patterns and establish relationships. Association rule mining is a well established method of data mining that identif...

We are developing a prototype intelligent intrusion detection system (IIDS) to demonstrate the effectiveness of data mining techniques that utilize fuzzy logic and genetic algorithms. This system combines both anomaly based intrusion detection using fuzzy data mining techniques and misuse detection using traditional rule-based expert system techniques. The anomaly-based components are developed...

Clustering algorithm is very important for data mining. Fuzzy c-means clustering algorithm is one of the earliest goal-function clustering algorithms, which has achieved much attention. This paper analyzes the lack of fuzzy C-means (FCM) algorithm and genetic clustering algorithm. Propose a hybrid clustering algorithm based on immune single genetic and fuzzy C-means. This algorithm uses the fuz...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW). Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and support se...

A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program is discussed. A genetic program (GP) is an algorithm that evolves other algorithms or mathematical expressions. Methods for accelerating convergence of the data mining procedure are examined. The methods include introducing fuzzy rules into the GP and a new innovation based on computer a...

This article proposes an algorithm for data mining that presents a new measure for assistance in the extraction of knowledge. The algorithm uses association rules to extract rules from the databases and fuzzy logic for the classification and comparison of the collected rules. Key-words: data mining, association rules, fuzzy logic, similarity and algorithm of the inverse confidence.

The fact of building an accurate classification and prediction system remains one of the most significant challenges in knowledge discovery and data mining. In this paper, a Knowledge Discovery (KD) framework is proposed; based on the integrated fuzzy approach, more specifically Fuzzy C-Means (FCM) and the new Multiple Support Classification Association Rules (MSCAR) algorithm. MSCAR is conside...