Research Paper on:
Machine Learning, Data Mining, and KM

Unformatted Sample Text from the Research Paper:
avoid disadvantageous positions. The role of information has changed since the introduction of the computer. Information was constrained by issues such as bounded rationality, limitations on memory and also  the time limitations that would be taken by analysing and retrieving information. However, with computers developing the ability to store and use data in electronic form many of the disadvantages  have been removed. The basic premise of the quality of the input will reflect the quality of the output is one that still holds true, however, with increasingly complex programmes  there are also increasing potential for the use of the data. Many databases of information are stored, but few are really maximised to enhance a business. The reason for this  is not the lack of existence of the data, but its inaccessibility. One of the methods that has been increasing in popularity is that of data mining. This is used  as a tool of knowledge management. This is a process that is used to mine information form databases, often different databases, in order to find information that can be used.  When this is taken a step further, and the information is then assimilated into patterns that can be adapted and changed as new information becomes available. This requires a dynamic  form of programmes that will facilitate machine learning. In this paper we will consider how the use of machine learning improve the way in which data mining is used to  add value to an organisation use of the information it already has. This is a wide area of research so will limit this to the consideration of banks, where data  mining may be seen as used on two separate but similar way, both of which are aimed at trying to predict the way a customer will behave in the future,