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

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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.