Amel Grissa Touzi | Searcharxiv

arXiv2015

Intelligent Implementation Processor Design for Oracle Distributed Databases System

Despite the increasing need for modeling and implementing Distributed Databases (DDB), distributed database management systems are still quite far from helping the designer to directly implement its BDD. Indeed, the fundamental principle of implementation of a DDB is to make the database appear as a centralized database, providing series of transparencies, something that is not provided directly by the current DDBMS. We focus in this work on Oracle DBMS which, despite its market dominance, offers only a few logical mechanisms to implement distribution. To remedy this problem, we propose a new architecture of DDBMS Oracle. The idea is based on extending it by an intelligent layer that provides: 1) creation of different types of fragmentation through a GUI for defining different sites geographically dispersed 2) allocation and replication of DB. The system must automatically generate SQL scripts for each site of the original configuration.

cs.DB↗

arXiv2013

Automatic ontology generation for data mining using fca and clustering

Motivated by the increased need for formalized representations of the domain of Data Mining, the success of using Formal Concept Analysis (FCA) and Ontology in several Computer Science fields, we present in this paper a new approach for automatic generation of Fuzzy Ontology of Data Mining (FODM), through the fusion of conceptual clustering, fuzzy logic, and FCA. In our approach, we propose to generate ontology taking in consideration another degree of granularity into the process of generation. Indeed, we suggest to define an ontology between classes resulting from a preliminary classification on the data. We prove that this approach optimize the definition of the ontology, offered a better interpretation of the data and optimized both the space memory and the execution time for exploiting this data.

cs.DB↗