Cognitive Computing and Big Data Analytics

CHAPTER 2 Design Principles for Cognitive Systems

In a cognitive computing system, the model refers to the corpus and the set of assumptions and algorithms that generate and score hypotheses to answer questions, solve problems, or discover new insights. How you model the world determines what kind of predictions you can make, patterns and anomalies you can detect, and actions you can take. The initial model is developed by the designers of the system, but the cognitive system will update the model and use the model to answer questions or provide insights. The corpus is the body of knowledge that machine learning algorithms use to continuously update that model based on its experience, which may include user feedback.

A cognitive system is designed to use a model of a domain to predict potential outcomes. Designing a cognitive system involves multiple steps. It requires an understanding of the available data, the types of questions that need to be asked, and the creation of a corpus comprehensive enough to support the generation of hypotheses about the domain based on observed facts. Therefore, a cognitive system is designed to create hypotheses from data, analyze alternative hypotheses, and determine the availability of supporting evidence to solve problems.

By leveraging machine learning algorithms, question analysis, and advanced analytics on relevant data, which may be structured or unstructured, a cognitive system can provide end users with a powerful approach to learning ...