The databases of real world contains a huge volume of data and among them there are
hidden piles of interesting relations that are actually very hard to find out. The knowledge …

The database of real world contains a huge volume of data and among them there are
hidden piles of interesting relations that are actually very hard to find out. The knowledge …

Presents a knowledge-oriented clustering method based on rough set theory. The method
evaluates the simplicity of classification knowledge during the clustering process and …

Knowledge management is fast becoming a commercial necessity for many organizations,
in order that they manage their intellectual assets and gain competitive advantage. To …

Rule-based knowledge bases are constantly increasing in volume, thus the knowledge
stored as a set of rules is getting progressively more complex and when rules are not …

Document clustering has been investigated for use in different areas of text mining and
information retrieval. A clustering depends on the chosen clustering algorithm as well as on …

In this paper, we present a particular study of the negative factors that affect the performance
of university students. The analysis is carried out using the CAI (Conjuntos Aproximados con …

We consider the problem of discovering the conceptual clusters from a large database. From
Z. Pawlak's information system in rough set theory, we define an information matrix …

Abstract Knowledge Discovery in Databases (KDD) is the nontrivial extraction of implicit,
previously unknown and potentially useful information from data. Data preprocessing is a …

Data mining and/or knowledge discovery is a very important part of today's e-business. The
World Wide Web has become in reality, the largest online information available practically to …