Applications Of Data Mining In E-business And Finance (frontiers In Artificial Intelligence And Applications)
by Z.-H. Zhou /
2008 / English / PDF
4.6 MB Download
The application of Data Mining (DM) technologies has shown an
explosive growth in an increasing number of different areas of
business, government and science. Two of the most important
business areas are finance, in particular in banks and insurance
companies, and e-business, such as web portals, e-commerce and ad
management services.In spite of the close relationship between
research and practice in Data Mining, it is not easy to find
information on some of the most important issues involved in real
world application of DM technology, from business and data
understanding to evaluation and deployment. Papers often describe
research that was developed without taking into account constraints
imposed by the motivating application. When these issues are taken
into account, they are frequently not discussed in detail because
the paper must focus on the method. Therefore knowledge that could
be useful for those who would like to apply the same approach on a
related problem is not shared. The papers in this book address some
of these issues. This book is of interest not only to Data Mining
researchers and practitioners, but also to students who wish to
have an idea of the practical issues involved in Data Mining.
The application of Data Mining (DM) technologies has shown an
explosive growth in an increasing number of different areas of
business, government and science. Two of the most important
business areas are finance, in particular in banks and insurance
companies, and e-business, such as web portals, e-commerce and ad
management services.In spite of the close relationship between
research and practice in Data Mining, it is not easy to find
information on some of the most important issues involved in real
world application of DM technology, from business and data
understanding to evaluation and deployment. Papers often describe
research that was developed without taking into account constraints
imposed by the motivating application. When these issues are taken
into account, they are frequently not discussed in detail because
the paper must focus on the method. Therefore knowledge that could
be useful for those who would like to apply the same approach on a
related problem is not shared. The papers in this book address some
of these issues. This book is of interest not only to Data Mining
researchers and practitioners, but also to students who wish to
have an idea of the practical issues involved in Data Mining.
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IOS Press is an international science, technical and medical
publisher of high-quality books for academics, scientists, and
professionals in all fields.
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