In point-of-interest recommendation for people with autism, standard preference-driven recommenders often misalign with sensory sensitivities and severe data scarcity, which can yield suggestions that are hard to trust and potentially harmful for everyday exploration. Knowledge-based reasoning and explanation mechanisms can enable more data-efficient, safety-aware personalization in this setting by explicitly modeling user–place sensory compatibility. Supporting …