Multidimensional Models of Information Need

User studies in information science have recognised relevance as a multidimensional construct. An implication of multidimensional relevance is that a user's information need should be modeled by multiple data structures to represent different relevance dimensions. While the extant literature has attempted to model multiple dimensions of a user's information need, the fundamental assumption that a multidimensional model is better than a uni-dimensional model has not been addressed. This study seeks to test this assumption. Our results indicate that a retrieval system that models both topicality and the novelty dimension of a users' information need outperforms a system with a uni-dimensional model.