The Use of Inductive Learning in Information Systems

Machine learning attempts to build computer programs that improve their performance by automating the acquisition of knowledge from experience. Inductive learning, one of machine learning paradigms, draws inductive inference from a teacher or environment-provided facts. Inductive learning enables the program to identify regularities and patterns in the prior knowledge or training data, and then to extract them as generalized rules. In literature there are proposed two ways of machine learning usage in information systems: (1) for building tools for software development and maintenance tasks and (2) for incorporation into software products to make them adaptive and self-configuring. However, considering information systems in more detail, division in three situations of inductive learning use in the context of information systems can be proposed, namely, first, in the information system development project management, second, to collect the information that is to be built in information system, third, to help the information system to adapt to the changing environment. The analysis of inductive learning role in information system development and usage is given. The future directions point to the e-commerce and similar domains on the Web for the role of inductive learning in information systems