This chapter discusses content-based recommendation systems, which recommend items to users based on item descriptions and user profiles. These systems are applicable in various domains, including web pages, news articles, restaurants, television programs, and e-commerce. The chapter outlines the common components of content-based recommendation systems: item representation, user profile creation, and item comparison. It begins with an introduction to modern recommendation systems, particularly those used in web applications, where users interact with a list of items and select specific ones for more details or interaction. The chapter then delves into different item representations, such as structured and unstructured data, and discusses the algorithms suitable for each representation. Finally, it covers variants of these approaches, their strengths and weaknesses, and future research directions.This chapter discusses content-based recommendation systems, which recommend items to users based on item descriptions and user profiles. These systems are applicable in various domains, including web pages, news articles, restaurants, television programs, and e-commerce. The chapter outlines the common components of content-based recommendation systems: item representation, user profile creation, and item comparison. It begins with an introduction to modern recommendation systems, particularly those used in web applications, where users interact with a list of items and select specific ones for more details or interaction. The chapter then delves into different item representations, such as structured and unstructured data, and discusses the algorithms suitable for each representation. Finally, it covers variants of these approaches, their strengths and weaknesses, and future research directions.