Towards open corpus adaptive hypermedia: A study of novelty detection approaches

Abstract

Classic adaptive hypermedia systems are able to track a user's knowledge of the subject and use it to evaluate the novelty and difficulty of content encountered by the user. Our goal is to implement this functionality in an open corpus context where a domain model is not available nor is the content indexed with domain concepts. We examine methods for novelty measurement based on automatic text analysis. To compare these methods, we use an evaluation approach based on knowledge encapsulated in the structure of a textbook. Our study shows that a knowledge accumulation method adopted from the domain of intelligent tutoring systems offers a more meaningful novelty measurement than methods adapted from the area of personalized information retrieval. © 2011 Springer-Verlag.