III-Core:Small: MoveMine: Mining Sophisticated Patterns and Actionable Knowledge from Massive Moving Object Data

III-核心：小：MoveMine：从海量移动对象数据中挖掘复杂的模式和可操作的知识

• 批准号: 1017362
• 负责人: Jiawei Han
• 金额: $ 50万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1017362&HistoricalAwards=false
• 关键词: III; Core; Small; MoveMine; Mining

This research project is to investigate principles and methods for uncovering sophisticated patterns and actionable knowledge from massive moving object data. Thanks to the rapid progress and broad adoption of sensor, GPS, wireless network, and other advanced technologies, moving object data have been accumulating in unprecedented scale. However, moving object data could be dynamic, sparse, scattered, and noisy, and patterns and knowledge to be mined could be deeply hidden, sophisticated, and subtle. The MoveMine project investigates effective and scalable methods for mining various kinds of complex patterns from dynamic and noisy moving object data, finding multiple interleaved periodic patterns, and performing in-depth multidimensional analysis of moving object data. It integrates and extends multiple disciplinary approaches derived from spatiotemporal data analysis, data mining, pattern recognition, statistics, and machine learning. The study takes bird and animal movement data and traffic data as the major sources of data for investigation. However, developed methods can be applied to the analysis of many other kinds of moving object data for environmental study, traffic control, law enforcement, and protection of homeland security. The study also addresses the issue of ensuring privacy and security protection while developing powerful pattern and knowledge discovery mechanisms. The research results are to be published in various research and application forums and be integrated into the educational programs at UIUC. The progress of the project and the research results are also disseminated via the project Web site (http://www.cs.uiuc.edu/homes/hanj/projs/movemine.htm).

本研究项目旨在研究从海量移动对象数据中揭示复杂模式和可操作知识的原理和方法。由于传感器、GPS、无线网络等先进技术的快速发展和广泛采用，运动物体数据以前所未有的规模积累。然而，移动对象数据可能是动态的、稀疏的、分散的和有噪声的，并且要挖掘的模式和知识可能是非常隐藏的、复杂的和微妙的。MoveMine项目研究了从动态和噪声移动对象数据中挖掘各种复杂模式的有效和可扩展的方法，发现多个交错的周期模式，并对移动对象数据进行深入的多维分析。它集成并扩展了来自时空数据分析、数据挖掘、模式识别、统计学和机器学习的多学科方法。本研究以鸟类和动物的运动数据和交通数据作为调查的主要数据来源。然而，所开发的方法可以应用于环境研究、交通控制、执法和国土安全保护等许多其他类型的移动物体数据的分析。该研究还解决了在开发强大的模式和知识发现机制的同时确保隐私和安全保护的问题。研究成果将在各种研究和应用论坛上发表，并纳入UIUC的教育项目。项目的进展和研究结果也通过项目网站（http://www.cs.uiuc.edu/homes/hanj/projs/movemine.htm）发布。