KNOT: Knowledge Discovery from Trajectory Data

KNOT：从轨迹数据发现知识

• 批准号: 418335-2013
• 负责人: Stefanakis, Emmanuel
• 金额: $ 0.95万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=665888
• 关键词: KNOT; Knowledge; Discovery; Trajectory; Data

In response to a strong expression of interest from the academic, industrial, and user communities, this proposal aims at performing a deep and sound research in the area of Knowledge Discovery from massive collections of trajectory data. The overall objective of the research is to develop innovating methods for processing, mining and disseminating useful knowledge from trajectory data. The research will mainly focus on the application area of Sea Vessel Traffic. A massive collection of historical datasets from both the Aegean Sea in the Mediterranean and the Saint Lawrence River in Canada as collected by various AIS Systems (e.g., marinetraffic.com), will be analyzed and tested.

为了回应学术界，工业界和用户社区的强烈兴趣，该提案旨在从大量轨迹数据中进行知识发现领域的深入和合理研究。研究的总体目标是开发创新方法，用于处理、挖掘和传播轨迹数据中的有用知识。研究将主要集中在海上船舶交通的应用领域。来自地中海爱琴海和加拿大圣劳伦斯河的大量历史数据集，由各种AIS系统收集（例如，marinetraffic.com），将进行分析和测试。