association rules are among important techniques in data mining which are used for extracting hidden patterns and knowledge in large volumes of data. association rules help individuals and organizations take strategic decisions and improve their business processes. extracted association rules from a database contain important and confidential information that if published, the privacy of indivi...

Dynamic data mining is increasingly attracting attention from the respective research community. On the other hand, users of installed data mining systems are also interested in the related techniques and will be even more since most of these installations will need to be updated in the future. For each data mining technique used, we need di1erent methodologies for dynamic data mining. In this ...

Image mining is more than just an extension of data mining to image domain. Image mining is a technique commonly used to extract knowledge directly from image. Image segmentation is the first step in image mining. We treat image segmentation as graph partitioning problem. In this paper we propose a novel algorithm, Minimum Spanning Tree based Structural Similarity Clustering for Image Mining wi...

Data mining is being applied with profit in many applications. Clustering or segmentation of data is an important data mining application. One of the problems with traditional clustering methods is that they require the analyst to define distance functions that are not always available. In this paper, we describe a new method for clustering without distance functions.

Data mining is being applied with profit in many applications. Clustering or segmentation of data is an important data mining application. One of the problems with traditional clustering methods is that they require the analyst to define distance functions that are not always available. In this paper, we describe a new method for clustering without distance functions.

Data mining is gaining importance due to huge amount of data available. Retrieving information from the warehouse is not only tedious but also difficult in some cases. The most important usage of data mining is customer segmentation in marketing, shopping cart analyzes, management of customer relationship, campaign management, Web usage mining, text mining, player tracking and so on. In data mi...

In this paper, we present the application of the fuzzy c-means clustering algorithm to the skin-color segmentation problem. We address the problem of identifying skin-color and we adapt a spatial data mining method to this task and integrate with a segmentation method to identify significant skin-color regions in an image. The proposed algorithm is able to take into account both the distributio...

We introduce an automated multi-spectral MRI segmentation technique based on approximate reducts derived from the data mining paradigm of the theory of rough sets. We utilized the T1, T2 and PD MRI images from the Simulated Brain Database as a ”gold standard” to train and test our segmentation algorithm. The results suggest that approximate reducts, used alone or in combination with other class...