Data Structures for Retrieval Problems (Computer and Information Science)

这个项目继续研究数据结构 这允许快速搜索。 一个主要的兴趣领域涉及 数据结构，用于快速扫描元素集以找到 位于特定几何区域中的子集，并且由此 更好地理解“范围查询”成本（从 当前软件需求的Vantage，潜在的几何 查询对象，动态设置，静态设置，权衡 在检索时间和记忆空间之间。 第二个目标是 继续研究如何有效地实施非程序化， 一种集合论数据库查询语言，类似于 函数演算或SETL，在主存数据库中。 其他领域 研究将包括可能的动态检查完美 散列，排序列表的紧凑表示和通信 并行处理中固有的延迟。 这一点的重要性 研究表明，几何区域搜索可以应用于 数据可以被映射的广泛区域 在空间-超大规模集成电路设计，图形设计接口， 人口普查或统计数据库应用程序 地区 高效检索，使用先进的技术，如 非常大的计算机主存储器，对于开发 这些应用程序。

This project continues research into data structures which allow fast searching. A major area of interest involves data structures for rapidly scanning set of elements to find the subset that lies in a particular geometric region, and to thereby develop a better understanding of "range query" costs (from the vantage points of current software needs, potential geometric query objects, a dynamic setting, a static setting, tradeoffs between retrieval time and memory space.) A second goal is to continue research into how to efficiency implement a non-procedu- ral set-theoretic database query language, similar to the rela- tional calculus or SETL, in a main memory database. Other areas of study will include possible examinations of dynamimc perfect hashing, compact representations of sorted lists and communication delays inherent in parallel processing. The importance of this research is that geometric region searching has applications into a wide range of area where the data can be though of as mapped out in space - VLSI circuit design, graphic-design interfaces, and census or statistical database applications based on geographical regions. Efficient retrieval, using advanced technology such as very large main memories for computer, is critical to developing these applications.