A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Interactive System Design
User Modeling and User-Adapted Interaction
Open corpus adaptive educational hypermedia
The adaptive web
A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques
Information Processing and Management: an International Journal
Slicepedia: automating the production of educational resources from open corpus content
EC-TEL'12 Proceedings of the 7th European conference on Technology Enhanced Learning
Slicepedia: towards long tail resource production through open corpus reuse
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
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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.