Knowledge management, knowledge discovery, and dynamic intelligent data mining

During the last two to three decades, many scientific as well business areas have moved from a situation of a lack of (electronically) readable information into a situation of abundant data. Data warehouses appeared, and the problem of extracting information from large masses of data became more and more important. Also knowledge became a very precious commodity, and its efficient use often makes the difference between success and failure. Finding useful information or patterns in raw data is known in the literature under various names, such as knowledge discovery in data bases, data mining, knowledge extraction, information discovery, information harvesting, data archaeology, etc. Many research areas, such as machine learning, pattern recognition, artificial intelligence, knowledge acquisition for expert systems, data visualization, and others are concerned with these activities, and the terminology used is not unequivocally defined. In this article, we shall first consider the different interpretations of the notions previously mentioned, and we shall then describe in more detail a recent technology that is very useful for data mining as well as for related areas.