III-COR-Small: Relational Data Community Discovery and Learning

该项目的目标是对一系列基本的、开放的、但非常重要的问题进行深入研究，从而形成一个统一的理论，包括关于一般关系数据社区发现和学习的革命性方法。具体方法包括统计机器学习和数据挖掘的新方法，统一的观点链接到机器学习和数据挖掘领域的现有文献。智力上的优点包括对一般无监督关系数据聚类和学习的全面理解的发展，以及在社区发现和学习方法方面的预期突破。更广泛的影响包括促进关系数据挖掘和统计机器学习的及时有效的知识传播，包括项目？网站（http://www.fortune.binghamton.edu/nsf-iis-0812114.htm），以及技术的开发和转让在广泛的应用。教育和拓展活动包括为大学生提供教育和研究经验。此外，活动强调推进和加强高中科学教育和教学大纲，并为高中的研究和为当地社区及其他地区提供服务开发一个综合模式。

The goal of this project is to conduct an in-depth research on a series of fundamental, open, but very important issues leading to the development of a unified theory consisting of revolutionary methods on the general relational data community discovery and learning. The specific approaches include novel methods on statistical machine learning and data mining with unified views to link to the existing literature in the areas of machine learning and data mining. The intellectual merit includes the development of comprehensive understanding of the general unsupervised relational data clustering and learning as well as the expected breakthrough in the community discovery and learning methodologies. The broader impacts include promoting the timely and effective knowledge dissemination on relational data mining and statistical machine learning, including project?s web site (http://www.fortune.binghamton.edu/nsf-iis-0812114.htm), as well as the technology development and transfer in a wide range of applications. Educational and outreach activities include providing educational and research experience for the university students. In addition, activities emphasize advancing and enhancing the high school education and syllabi in sciences and developing an integrated model for high schools' research and services for the local community and beyond.