CLEAR：一种以知识为中心的船舶轨迹分析平台
CLEAR: A Knowledge-Centric Vessel Trajectory Analysis Platform
AI总结：
CLEAR平台利用大语言模型生成能力，将不完整复杂的AIS数据转化为完整可解释的船舶轨迹，通过结构化数据知识图谱提升非专业用户分析能力。
摘要：
船舶轨迹数据从自动识别系统（AIS）广泛用于海洋分析。然而，由于AIS数据的不完整性和复杂性，非专业用户进行分析存在困难。我们提出了CLEAR，一种以知识为中心的船舶轨迹分析平台，旨在克服这些障碍。通过利用大语言模型（LLMs）的推理和生成能力，CLEAR通过结构化数据衍生的知识图谱（SD-KG）将原始AIS数据转换为完整、可解释且易于探索的船舶轨迹。作为演示的一部分，参与者可以配置参数自动下载和处理AIS数据，观察轨迹如何完成和注释，检查原始和补充分段及其SD-KG证据，并通过专用图查看器交互式探索SD-KG，从而获得对船舶运动的直观透明理解。
英文摘要：
Vessel trajectory data from the Automatic Identification System (AIS) is used widely in maritime analytics. Yet, analysis is difficult for non-expert users due to the incompleteness and complexity of AIS data. We present CLEAR, a knowledge-centric vessel trajectory analysis platform that aims to overcome these barriers. By leveraging the reasoning and generative capabilities of Large Language Models (LLMs), CLEAR transforms raw AIS data into complete, interpretable, and easily explorable vessel trajectories through a Structured Data-derived Knowledge Graph (SD-KG). As part of the demo, participants can configure parameters to automatically download and process AIS data, observe how trajectories are completed and annotated, inspect both raw and imputed segments together with their SD-KG evidence, and interactively explore the SD-KG through a dedicated graph viewer, gaining an intuitive and transparent understanding of vessel movements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
