This paper proposes a simple, automatic and efficient clustering algorithm, namely, Automatic Merging for Optimal Clusters (AMOC) which aims to generate nearly optimal clusters for the given datasets automatically. The AMOC is an extension to standard k-means with a two phase iterative procedure combining certain validation techniques in order to find optimal clusters with automation of merging...

Web mining is the application of data mining technology to discover patterns from the web. The various tasks on web such as relation extraction, community mining, document clustering and automatic metadata extraction. A previously proposed web-based semantic similarity measures on three benchmark datasets showing high correlation with human rating. One of the main problems in information retrie...

In previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on semantic features. We show, in contrast with previous work, that considerable additional improvement can be obtained by using semantic features in automatic classification: verb selectional preferences acquired from corpus data using a f...

Image segmentation plays an important role in medical imaging applications. In this chapter, an automatic MRI brain image segmentation framework using gravitational search based clustering technique has been proposed. This framework consists of two stage segmentation procedure. First, non-brain tissues are removed from the brain tissues using modified skull-stripping algorithm. Thereafter, the ...

We present a two-step process including white matter atlas generation and automatic segmentation. Our atlas generation method is based on population fiber clustering. We produce an atlas which contains high-dimensional descriptors of fiber bundles as well as anatomical label information. We use the atlas to automatically segment tractography in the white matter of novel subjects and we present ...

A novel data-analysis tool incorporated with an interactive visualization and an automatic clustering was developed. The tool specializes in variance analysis, especially in handling a large volume of clinical-process data from plural patients. The interactive visualization enables users to identify outliers and variance to improve clinical process and homogeneous processes to develop critical ...

Metadata are data about data. Geographical metadata describe geospatial data: maps, satellite images or other geographically referenced material. The two characteristics of geographical metadata, high dimensionality and diversity of attribute data types, present a problem for automatic data mining. We present an approach for exploration of geographical metadata which is based on an integration ...

This paper presents a new approach for the automatic generation of fuzzy rule bases for pattern recognition. The general idea of the approach is to use and enhance the fuzzy c-means clustering algorithm. The rule base is generated through an iterative feature clustering approach. The automatic extraction of features is repeated until the generated rule base is giving an unequivocal answer. Alth...