Browsing by Author "Joentausta, Jussi"

As the amount of information available on the Internet keeps growing new problems arise. The abundance of information makes it more difficult to find proper, needed content in a timely manner. Recommender systems have been developed as an answer to the problem. They aim to provide relevant information to the user. This thesis presents how information can be described, how information retrieval works in general and how recommender systems work. The operation of recommender systems is based on finding similarities between contents and between users. By combining these recommender systems try to estimate what kind of information would be most suitable for the user at specific moment. In the research section a content-based recommender was built for a website. The aim of the research was to find out whether it is possible to extract keywords and create recommendations with the method chosen for the research. Quality of the extracted keywords was measured by a survey and the recommender system as a whole was piloted on a website. Based on the research results extraction of keywords and creation of recommendations were, on average, successful.