A Model-View-Controller Architecture for Knowledge Discovery

In this paper we present a flexible mining architecture able to define and validate a process, generally applicable in different e-business sectors, for providing new added value e-Knowledge services. The architecture is designed on the Model-View-Controller pattern in order to get a clear separation of the component functionalities and covers the whole process of Knowledge Discovery in Databases (KDD) and in Text (KDT) for the extraction of patterns starting from structured and unstructured data. When a service request comes to the system, this is received by a Controller that will call one or more Miners to provide the results. The Miners represent the Model of the system and, by using a Kernel, dynamically activate either the KDD or the KDT process, depending on the typology of the service. As View, the system makes use of the CWM standard for the representation of metadata about models and results of the mining processes. The Kernel includes two different Focuses, for the selection of structured and unstructured data. The results of the Focuses are passed to a unique Pattern Extraction step, where Web and Data Mining algorithms are collected for the analysis. Finally, an Evaluation step interprets the utility of the extracted patterns. The proposed solutions can be suited in a distributed mining environment, where a set of services are managed and made available as a means of meeting the diverse needs of the e-business world.