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.
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