Interoperability between platforms without a defined referential model: A semi-automatic learning system for structural pairing

This paper deals with the exchange of information between universities problematic, but could influence other sectors like banking, health, etc. where there are not standards defined for information exchange. We propose a semi-automatic learning and assessment system that is capable of unifying the way in which each of the universities work by employing a three-step system that will be based on the exploitation of the information offered by the web services in their WSDL files and the way in which each of the universities that had been previously evaluated work. This three-step system would be focused on: (a) taking advantage of the information that is obtained on a structural level from the WSDL, which, using the String-Metrics (Cohen, Ravikumar, & Fienberg, 2003) application, will be able to connect the structures between universities, (b) reinforcing any prior knowledge with a classification system for cases that could not be matched, and (c) applying a reasoning system or rules to support the previous two steps. The main result obtained is a system that is able to interoperate two or more platforms between themselves to automatically share information in spite of their structural difference.