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

信息存在于许多不同的位置，并以许多不同的格式存在，但需要收集和汇总这些信息。 一个重要的未解决的问题仍然是：如何聚合的信息时，查询规则的理解不足，非正式的状态，快速变化，或者当有必要选择性的敏感信息的启示。 这个项目将探索使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。一个框架的异常检测已经开发和新的连接发现，证明了在这个框架中的计算在关系数据库中的无损连接的形式等价。 这提供了一种可能性，数据库查询系统可以建立具有基于免疫的属性的分布式，适应性和灵活性。 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满足分布式系统的挑战。 它还将延伸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.