标题： RailEstate：一种用于地铁关联房产趋势的交互系统 显示英文标题

标题： RailEstate: An Interactive System for Metro Linked Property Trends

摘要： 地铁系统的接入在塑造城市住房市场中起着关键作用，通过提高社区的可达性并推动房产需求。 我们提出了RailEstate，一个基于网络的新系统，它整合了空间分析、自然语言接口和交互式预测，以分析地铁站附近对住宅物业价格的影响。 与静态地图工具或通用列表平台不同，RailEstate结合了25年的历史住房数据和交通基础设施，以支持低延迟的空间地理查询、时间序列可视化和预测建模。 用户可以交互式地探索邮编级别的价格模式，研究长期趋势，并预测任何地铁站周围的未来住房价值。 一个关键的创新是我们自然语言聊天机器人，它可以将普通的英语问题，例如“2000年Falls Church的最高价格是多少？”转换为对空间数据库的可执行SQL。 这个统一且交互式的平台使城市规划者、投资者和居民能够从地铁连接的住房数据中获得可操作的见解，而无需技术专业知识。 显示英文摘要

摘要： Access to metro systems plays a critical role in shaping urban housing markets by enhancing neighborhood accessibility and driving property demand. We present RailEstate, a novel web based system that integrates spatial analytics, natural language interfaces, and interactive forecasting to analyze how proximity to metro stations influences residential property prices in the Washington metropolitan area. Unlike static mapping tools or generic listing platforms, RailEstate combines 25 years of historical housing data with transit infrastructure to support low latency geospatial queries, time series visualizations, and predictive modeling. Users can interactively explore ZIP code level price patterns, investigate long term trends, and forecast future housing values around any metro station. A key innovation is our natural language chatbot, which translates plain-English questions e.g., What is the highest price in Falls Church in the year 2000? into executable SQL over a spatial database. This unified and interactive platform empowers urban planners, investors, and residents to derive actionable insights from metro linked housing data without requiring technical expertise.