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This paper describes a hybrid dialogue system for restaurant recommendation and reservation. The proposed system combines rule-based and data-driven components by using a flexible architecture aiming at diminishing error propagation along the different steps of the dialogue management and processing pipeline. The system implements three basic subsystems for restaurant recommendation, selection and booking, which leverage on the same system architecture and processing components. The specific system described here operates with a data collection of Singapore's F&B industry but it can be easily adapted to any other city or location by simply replacing the used data collection.
Kim et al. (Mon,) studied this question.