Join this immersive workshop, where you’ll delve into case-based reasoning (CBR) and also explore additional powerful techniques of collaborative filtering and content-based filtering used to create intelligent information systems. Case-based reasoning is a problem-solving methodology that relies on past experiences (cases) to guide future decision-making. Similarly, collaborative filtering and content-based filtering are key methodologies in developing recommender systems, widely used by platforms such as Netflix and YouTube to personalize user experiences.

In this workshop, you will gain hands-on experience using the Intellikit framework and understand how a case-based reasoner matches new problems to “cases” from a historical database, adapting successful solutions from the past to current situations. Additionally, you will learn how collaborative filtering leverages user interactions and preferences to make recommendations, while content-based filtering focuses on the attributes of items to suggest similar ones.

Organisations as diverse as IBM, VISA International, Volkswagen, British Airways, and NASA have already used CBR in applications such as customer support, quality assurance, aircraft maintenance, process planning, and decision support, and many more applications are easily imaginable. Similarly, recommender systems can be embedded in platforms like Jumia to enhance the shopping experience by providing personalized product suggestions. It is relatively simple to add CBR and recommender system components to existing information systems, making them versatile and highly beneficial tools for various industries.