Current database technology and computer hardware allow us to  gather, store, access, and manipulate massive volumes of raw data in  an efficient and inexpensive manner. In addition, the amount of data  collected and warehoused in all industries is growing every year at a  phenomenal rate. Nevertheless, our ability to discover critical,  non-obvious nuggets of useful information in data that could influence  or help in the decision making process, is still limited.   Knowledge discovery (KDD) and Data Mining (DM) is a new,  multidisciplinary field that focuses on the overall process of  information discovery from large volumes of data. The field combines  database concepts and theory, machine learning, pattern recognition,  statistics, artificial intelligence, uncertainty management, and  high-performance computing.   To remain competitive, businesses must apply data mining techniques  such as classification, prediction, and clustering using tools such as  neural networks, fuzzy logic, and decision trees to facilitate making  strategic decisions on a daily basis.   Knowledge Discovery for Business Information Systems contains a  collection of 16 high quality articles written by experts in the KDD  and DM field from the following countries: Austria, Australia,  Bulgaria, Canada, China (Hong Kong), Estonia, Denmark, Germany, Italy,  Poland, Singapore and USA.

Knowledge Discovery for Business Information Systems (The Kluwer International Series in Engineering and Computer Science Volume 600) PDF

The list of books you might like