DIRECT AND SUPPLEMENTARY SHADOWS IN THE TASK OF THE EFFICIENT DESCRIPTION OF CLASSES

One of the best techniques of feature efficiency estimation is based on the application of composition of the binary relations, i.e. direct shadows of fuzzy sets. Furthermore, the analysis of the binary relations yields a significant increase in the efficiency of the method operation, and also a detailed understanding of the processes occurring during the process of composition under various conditions.Since the composition of the binary relations is exploited to estimate the efficiency of attributes by means of direct shadows of fuzzy sets, a question appears: what volume of the information regarding the efficiency of attributes can supplementary shadows of fuzzy sets bear ? The use of supplementary shadows along with the analysis of direct shadows of fuzzy sets will presumably give a more complete representation about the efficiency of features of classes.The experiments performed on solving tasks by means of the composition of direct and supplementary shadows have shown that imder certain conditions supplementary shadows can give some auxiliary estimation of the attributes efficiency. It was then decided to continue some of experiments to reveal the valid behavior of supplementary shadows under various statements of the task and various samples, and also provided that the quantity of classes and the degree of their participation in space were changed.In this paper, an example is considered where three classes participate on a three-dimensional space of attributes. The convolution of composition realization results, degrees of reduction, is also proposed to estimate the attributes available

Conceptual design and implementation of the fuzzy semantic model

FSM is one of few database models that support fuzziness, uncertainty and impreciseness of real-world at the class definition level. FSM authorizes an entity to be partially member of its class according to a given degree of membership that reflects the level to which the entity verifies the extent properties of this class. This paper deals with the conceptual design of FSM and adresses some implementation issues.ou

Implementing imperfect information in fuzzy databases

Information in real-world applications is often vague, imprecise and uncertain. Ignoring the inherent imperfect nature of real-world will undoubtedly introduce some deformation of human perception of real-world and may eliminate several substantial information, which may be very useful in several data-intensive applications. In database context, several fuzzy database models have been proposed. In these works, fuzziness is introduced at different levels. Common to all these proposals is the support of fuzziness at the attribute level. This paper proposes first a rich set of data types devoted to model the different kinds of imperfect information. The paper then proposes a formal approach to implement these data types. The proposed approach was implemented within a relational object database model but it is generic enough to be incorporated into other database models.ou

Training a personal alert system for research information recommendation

Information Systems, and in particular Current Research Information Systems (CRISs), are usually quite difficult to query when looking for specific information, due to the huge amounts of data they contain. To solve this problem, we propose to use a personal search agent that uses fuzzy and rough sets to inform the user about newly available information. Additionally, in order to automate the operation of our solution and to provide it with sufficient information, a document classification module is developed and tested. This module also generates fuzzy relations between research domains that are used by the agent during the mapping process