SGER: Reconstructing Information from Database Fragments Via Negative Partial Match Detection

信息以许多不同的格式存在于许多不同的位置，但是需要收集汇总这些信息。一个重要的未解决的问题仍然存在：当查询规则难以理解、状态非正式、变化迅速或需要选择性地披露敏感信息时，如何聚合信息。该项目将探索利用免疫系统的思想和算法来解决数据库问题的可能性，例如这种自适应查询问题。开发了一个异常检测框架，并发现了新的连接，证明了该框架中的计算与关系数据库中的无损连接的形式等价。这为构建具有分布式、适应性和灵活性的基于免疫的数据库查询系统提供了可能。这里提出的方法是激进的，有点投机，但如果成功，可以帮助数据库技术应对分布式系统的挑战。它还将扩展生物学和计算之间的桥梁。这项工作将涉及一个指定的少数民族机构。

Information resides in many different locations and in many different formats, but there is a need to collect an aggregate this information. An important unsolved problem remains: How to aggregate the information when the query rules are poorly understood, informally state, changing quickly, or when there is a need for selective revelation of sensitive information. This project will explore the possibility of using ideas and algorithms from the immune system to address database issues such as this adaptive query problem. A framework for anomaly-detection has been developed and anew connection found that demonstrates the formal equivalence of the computations in this framework to lossless joins in relational databases. This offers the possibility that a database query system can be built to have immune-based properties of distributivity, adaptability and flexibility. The approach proposed here is radical and somewhat speculative, but if successful, could help database technology meet the challenges of distributed system. It will also extend the bridge between biology and computation. The work will involve a designated minority institution.