Knowledge representation and reasoning play key role in automated decision support as many of the problems machines are expected to solve will require extensive knowledge about the world. In the area of AI (artificial intelligence) research two complementary approaches, rule-based reasoning and case-based reasoning are widely used for building knowledge-based “intelligent” decision-support systems. We will describe the basic principles of both approaches, their strengths and limitations and show how these approaches can be used for sentiment analysis