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.

Mining spatial association rules is one of the most important branches in the field of Spatial Data Mining (SDM). Because of the complexity of spatial data, a traditional method in extracting spatial association rules is to transform spatial database into general transaction database. The Apriori algorithm is one of the most commonly used methods in mining association rules at present. But a sh...

This paper presents a methodology for knowledge acquisition from source code. We use data mining to support semiautomated software maintenance and comprehension and provide practical insights into systems specifics, assuming one has limited prior familiarity with these systems. We propose a methodology and an associated model for extracting information from object oriented code by applying clus...

Association rules mining approach can find the relationship among items. Using association rules mining algorithm to mine resource fault, can reduce the number of wrong alarm resources to be replaced. This paper proposed an efficient association rules mining algorithm: CSRule, for mining closed strong association rules based on association rule merging strategies. CSRule algorithm adopts severa...

In this paper, the investment portfolio is formed based on the data mining algorithm of CHAID on the basis of the risk status criteria. In the next step, the second investment portfolio is created based on the decision rules extracted by the DEA-BCC model. The final portfolio is created through a two-objective mathematical programming model based on the Imperialist Competitive algorithm.

Association Rule play very important role in recent scenario of data mining. But we have only generated positive rule, negative rule also useful in today data mining task. In this paper we are proposing “A new method for generating all positive and negative Association Rules” (NRGA).NRGA generates all association rules which are hidden when we have applied Apriori Algorithm. For representation ...