Benjamín López Pérez

Interoperability between platforms without a defined referential model

Interoperable information system for models within the same sector.The information will be shared through information models, Web Services.It is a low-cost, providing in the end a semi-automatic self-learning solution.The system is capable of interoperate a three-step matching process.The system lacks enough information, it will require human intervention. 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.

Dynamic Generation of Interactive Dialogs Based on Intelligent Agents

The design of the lexical and syntactical levels of the user interface of any web based system is commonly based on general human-computer interaction principles targeted to match the interaction requirements of the so-called typical user, an abstract generalization of each user of an application. However the identification of such typical user at the web design stage seems to be an impossible task, considering the dynamic nature of the web, where the user interface of a popular web systems can be used by thousands of different users everyday. In order to avoid this problem, we have designed GADEA, an intelligent user interface management system able to detect different kinds of users by mean of distributed data gathering agents. The information obtained by those agents is used to design interactive dialogues at execution time, which are adapted to the specific cognitive, perceptive and motor characteristics of the current user.