Abstract
Supporting conversational approaches in mobile recommender systems is challenging because of the inherent limitations of mobile devices and the dependence of produced recommendations on the context. In a previous work, we proposed a critique-based mobile recommendation approach and presented the results of a live users evaluation. Live-user evaluations are expensive and there we could not compare different system variants to check all our research hypotheses. In this paper, we present an innovative simulation methodology and its use in the comparison of different user-query representation approaches. Our simulation test procedure replays off-line, against different system variants, interactions recorded in the live-user evaluation. The results of the simulation tests show that the composite query representation, which employs both logical and similarity queries, does improve the recommendation performance over a representation using either a logical or a similarity query.