Knowledge-based Clustering, Indo-U.S. Collaborative Research. Award In U.S. and Indian Currencies

基于知识的聚类，印度-美国

• 批准号: 9321584
• 负责人: Anil Jain
• 金额: $ 1.98万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-05-15 至 1998-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9321584&HistoricalAwards=false
• 关键词: Knowledge; based; Clustering; Indo; U.S.

9321584 Jain Description: This project is to support collaboration by Dr. Anil K. Jain of the Department of Computer Science at Michigan State University, and Dr. M. Narasimha Murty of the Department of Computer Science and Automation at the Indian Institute of Science in Bangalore, India. The two scientists will work jointly in the area of knowledge-based clustering. The main focus of the research will be the following topics: incorporate domain knowledge to obtain more meaningful clusters; investigate grouping of labelled objects for efficient representation and rule generation; and develop tools to assist a potential user in selecting an appropriate clustering algorithm for a given problem. Scope: Cluster analysis attempts to assess the interaction among patterns by organizing the patterns into groups or clusters such that patterns within a cluster are more similar to each other than patterns belonging to different clusters. The results can be used to initiate hypotheses about the data. The method is popular in pattern recognition, computer vision, machine learning, biology, psychiatry, psychology, marketing, and information retrieval. The collaboration by these two highly competent scientists should advance the techniques used and lead to better utilization of the method. ***

9321584 Jain描述：该项目支持密歇根州立大学计算机科学系的Anil K. Jain博士和印度班加罗尔印度科学研究所计算机科学与自动化系的M. Narasimha Murty博士的合作。两位科学家将在基于知识的聚类领域进行合作。研究的重点将集中在以下几个方面：整合领域知识以获得更有意义的聚类；研究标记对象的分组，以便有效地表示和生成规则；并开发工具来帮助潜在用户为给定问题选择合适的聚类算法。范围：聚类分析试图通过将模式组织成组或集群来评估模式之间的交互作用，这样集群内的模式比属于不同集群的模式更相似。结果可以用来提出关于数据的假设。该方法在模式识别、计算机视觉、机器学习、生物学、精神病学、心理学、市场营销和信息检索等领域都很流行。这两位非常有能力的科学家的合作应该会推进所使用的技术，并导致更好地利用该方法。＊＊＊