标题： CityHood：一种可解释的城市和社区旅行推荐系统 显示英文标题

标题： CityHood: An Explainable Travel Recommender System for Cities and Neighborhoods

摘要： 我们提出CityHood，一个交互式且可解释的推荐系统，该系统根据用户的兴趣领域推荐城市和社区。 该系统通过利用大规模Google Places评论来建模用户兴趣，并结合地理、社会人口、政治和文化指标进行增强。 它在城市（基于核心统计区 - CBSAs）和社区（邮政编码）层面提供个性化推荐，并由一种可解释技术（LIME）和自然语言解释支持。 用户可以根据其明确偏好探索推荐内容，并通过可视化界面检查每个建议背后的推理过程。 演示展示了如何利用空间相似性、文化契合度和兴趣理解来使旅行推荐透明且具有吸引力。 这项工作通过在面向用户系统中结合兴趣建模、多尺度分析和可解释性，弥合了基于位置推荐中的差距。 显示英文摘要

摘要： We present CityHood, an interactive and explainable recommendation system that suggests cities and neighborhoods based on users' areas of interest. The system models user interests leveraging large-scale Google Places reviews enriched with geographic, socio-demographic, political, and cultural indicators. It provides personalized recommendations at city (Core-Based Statistical Areas - CBSAs) and neighborhood (ZIP code) levels, supported by an explainable technique (LIME) and natural-language explanations. Users can explore recommendations based on their stated preferences and inspect the reasoning behind each suggestion through a visual interface. The demo illustrates how spatial similarity, cultural alignment, and interest understanding can be used to make travel recommendations transparent and engaging. This work bridges gaps in location-based recommendation by combining a kind of interest modeling, multi-scale analysis, and explainability in a user-facing system.