Mining patterns from fuzzy temporal data is an important data mining problem. One of these mining task is to find locally frequent sets, In most of the earlier works fuzziness was considered in the time attribute of the datasets .Although a couple of works have been done in dealing with such data, little has been done on the implementation side. In this article, we propose an efficient implemen...

A fuzzy spatial data mining technique has been developed to extract relationships describing relative position of classes of objects from raster images. Several different rule forms are described which represent different types of directional relationships between classes of objects. The method has been tested with hand-generated, synthetic, and sonar imagery.

Data mining methods including association rule mining and frequent episode mining have been applied to the intrusion detection problem. In other work, we have introduced modifications of these methods that mine fuzzy association rules and fuzzy frequent episodes and have described off-line methods that utilize these fuzzy methods for anomaly detection from audit data. In this paper we describe ...

It is estimated that every 20 months or so the amount of information in the world doubles. In the same way, tools that mine knowledge from data must develop to combat this growth. Such techniques must be able to extract useful, meaningful patterns efficiently in the presence of large amounts of noisy, redundant and sometimes misleading information. To be able to achieve this, data mining is oft...

In order to analyze vague data set of uncertainty information, Fuzzy Formal Concept Analysis(FFCA) incorporates fuzzy set theory into Formal Concept Analysis(FCA). It extracts useful information with a unit of fuzzy concept from given fuzzy formal context with a confidence threshold. Then it constructs fuzzy lattice by order relations between the fuzzy concepts. In this paper, we introduce basi...

Data mining is the analysis step of the "Knowledge Discovery in Databases" process, or KDD. It is the process that results in the discovery of new patterns in large data sets. It utilizes methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract knowledge from an existing data set and tra...

This report explores integrating fuzzy logic with two data mining methods (association rules and frequency episodes) for intrusion detection. Data mining methods are capable of extracting patterns automatically from a large amount of data. The integration with fuzzy logic can produce more abstract and flexible patterns for intrusion detection, since many quantitative features are involved in in...