Information Technology: Data Mining

1.1. DATA MINING Data mining refers to extracting or mining knowledge from large amounts of data. Data mining has attracted a great deal of attention in the information industry and in society as a whole in recent years, due to the wide availability of huge amounts of data and the forthcoming need for turning such data into useful information and knowledge. The information and knowledge gained can be used for applications ranging from market analysis, fraud detection, and customer retention, to production control and science exploration. Data mining can be viewed as a result of the natural evolution of information technology. The database system industry has witnessed an evolutionary path in the development of the following functionalities

IMAGE MINING Image Mining is an extended branch of data mining that is concerned with the process of knowledge discovery from images. Image mining deals with the extraction of image patterns from a large collection of images. It can be done manually by slicing and dicing the data until a pattern becomes obvious. Or, it can be done with programs that analyze the data automatically. Color, texture and shape of an image have been primitive image descriptors in Content Based Image Retrieval (CBIR) system. Primitive features of an image are used to identify and retrieve closely matched images from an image database. It is very difficult to extract images manually from image database because they are very large. Mining useful content from image collections is very much an interdisciplinary endeavor that draws upon expertise in computer vision, image understanding, data mining, machine learning, databases, distributed/parallel computing, software design, and artificial

Image mining draws basic principles from concepts in databases, machine learning, statistics, pattern recognition and 'soft' computing. Image mining is focused on extracting patterns, implicit knowledge, image data relationship or patterns which are not explicitly found in the images from databases or collections of images. Some of the methods used to gather knowledge are: image retrieval, data mining, image processing and artificial intelligence. These methods allow image mining to have two different approaches. First, is to extract only from databases or collections of images, and second, dig or mine a combination of associated alphanumeric data and collections of images. Image miners are capable of using existing techniques in order to mine for knowledge. Some of these techniques