Information extraction in business intelligence systems

Business intelligence plays a key role in many business systems by enabling easier and quicker decision-making. The strength of business intelligence system is directly dependent of source data and it's availability. This paper analyzes alternatives to usage of strictly structured data. Text mining systems can function independently but can also be considered as just one step in larger information systems. Combination of business intelligence with information extraction methods can significantly improve data set used for analysis with the result of enlarged knowledge base for decision-making. This paper gives an overview of many proposed sets of techniques for information extraction but focuses on machine learning as the most promising one. In order to minimize human effort necessary for machine learning but also to gain satisfying results the optimal choice would be weakly supervised machine learning techniques.