A Logic Programming Approach to Integration Network Inference
This addresses the challenge of gaining visibility into integration networks for enterprises, but it appears incremental as it applies an existing method (logic programming) to a specific domain problem.
The authors tackled the problem of reconstructing integration networks from Network Mining raw data in complex enterprise IT landscapes by using a logic programming approach based on first-order logic, and they built a system applied to real-world scenarios to report on their experience.
The discovery, representation and reconstruction of (technical) integration networks from Network Mining (NM) raw data is a difficult problem for enterprises. This is due to large and complex IT landscapes within and across enterprise boundaries, heterogeneous technology stacks, and fragmented data. To remain competitive, visibility into the enterprise and partner IT networks on different, interrelated abstraction levels is desirable. We present an approach to represent and reconstruct the integration networks from NM raw data using logic programming based on first-order logic. The raw data expressed as integration network model is represented as facts, on which rules are applied to reconstruct the network. We have built a system that is used to apply this approach to real-world enterprise landscapes and we report on our experience with this system.