We present CiRi-Engine (CityRiddler Recommendation Engine), an interactive city walking-tour recommender system. This demonstration paper showcases a novel approach to generating personalized and balanced itineraries for urban exploration. By combining user-specified constraints, such as start and end locations, tour duration, interest categories, and challenge preferences, with an efficient dual-stage routing algorithm, CiRi-Engine dynamically constructs diverse routes featuring curated Points of Interest (POIs). The engine leverages a novel hybrid of A* and Beam Search for path planning, and incorporates preference-aware POI selection to ensure both relevance and diversity. We demonstrate firsthand how the system balances route diversity, thematic coherence, and user-specified constraints, demonstrating its effectiveness for handling multiple objectives and generating engaging walking tours.
Zamiechowska et al. (Wed,) studied this question.
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