Data base management evolved during the sixties and seventies. The evolution period was protracted. Many driving forces impacted the evolution and it is the aim of this paper to analyze these driving forces (some technical and some political) and to…

This paper shows models of data description that incorporate uncertainty like models of data extension EER, IFO among others. These database modeling tools are compared with the pattern FuzzyEER proposed by us, which is an extension of the EER model…

Nowadays, data intensive applications are in constant demand and there is need of computing environments with better intelligent capabilities than those present in today's Database Management Systems (DBMS). To build such systems we need formalisms that can perform complicate inferences,…

This paper presents a data structure based on Sparse Spatial Selection (SSS) for similarity searching. An algorithm that tries periodically to adjust pivots to the use of database index is presented. This index is dynamic. In this way, it is…

Knowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In…

When stakeholders are geographically distributed communication presents new challenges for software engineering community. In order to improve communication between stakeholders, we have previously proposed to apply learning style models to characterise the way people interact. In this work we enhance…

This document describes a research and development project - Semantic Web and Cooperative Problem Solving for Online Communities of Practice. The aim of the project is to build a system supporting Cooperative Problem Solving within the framework of online Communities…

The concept of “approximate” searching has applications in a vast number of fields. Some examples are non-traditional databases (e. g. storing images, fingerprints or audio clips, where the concept of exact search is of no use and we search instead…

In cases of extremely imbalanced dataset with high dimensions, standard machine learning techniques tend to be overwhelmed by the large classes. This paper rebalances skewed datasets by compressing the majority class. This approach combines Vector Quantization and Support Vector Machine…

A methodology was developed for analysing faults in distribution transformers using the statistical package for social sciences (SPSS); it consisted of organising and creating of database regarding failed equipment, incorporating such data into the processing programme and converting all the…