NYI: Parallel Algorithms for Information Retrieval

在未来几年内，全球信息系统将处理数千个单独站点每天生成的数千兆字节数据的收集解释。 在这样一个异构分布式数据库系统中定位数据，无异于为全球大海捞针提供资金。 为了实现这一目标，正在开发基于对所收集数据的类型和量级的理解以及对数据执行的查询的类型和相对频率的适当的数据模型。 需要用于对多方面数据进行并行搜索、索引和压缩的算法。 同样必要的是用于在构成整个搜索空间的许多节点之间进行通信的协议。 这些协议必须允许在各种平台之间高效、可靠且安全地分发查询和结果。 开发了每个数据存储站点的多计算机搜索引擎。 一组合作者使用原型进行评估，他们的反馈将被纳入最终的实施中。 这项研究获得的结果可以作为全球范围内刚性和松散结构数据库的开发指南。

Within the next several years, worldwide information systems will deal with the collection interpretation of several gigabytes of data generated daily at thousands of individual sites. Locating data in such a heterogeneous distributed-database system, is tantamount to funding the proverbial needle in a worldwide haystack. To accomplish this endeavor, an appropriate data model based on an understanding of the type and magnitude of the data collected and on the type and relative frequency of the queries to be performed on the data are being developed. Algorithms for conducting parallel searches, indexing, and compression of the multi-faceted data are required. Also necessary are the protocols for communicating among the many nodes that constitute the entire search space. These protocols must allow for efficient, reliable, and secure distribution of queries and results among a variety of platforms. Multicomputer search engines at each data storage site are developed. A set of collaborators employs the prototype for evaluation and their feedback will be incorporated into the final implementation. The results obtained in this research may serve as a guideline for the development of worldwide both rigidly and loosely structured databases.