Abstract
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.
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