Tutoring Library System using Case- Based Reasoning

Abstract

This paper proposes a tutoring library system based on case-based reasoning approach for library users. Each case in the case library is represented in terms of presuggested set of chapters from different books in general. This system retrieves the most similar cases from the case library using the nearest neighbor algorithm. Since many cases at the same time can be similar to the user request, the possibility will exist to combine the corresponding solutions in an efficient way to find the final solution, compositional adaptation is applied and the set of chapters that would satisfy the user request is presented by percentage. By using the tutoring library system, there would be no need for the users to refer to the experts and this system can suggest the user an appropriate combination of the chapters from different books. This system suggests the solution to the user that provides a suitable ground to take into account a variety of factors such as current knowledge level and the desired status of knowledge.