SisAC - Sistema de Auxílio à Classificação. Estudo de caso: Ostracode

Abstract

The constant increase in the volume of information of several areas of knowledge, through the production of bibliographic, multimedia and web material, is a result of advancements of research and scientific studies, and has led to issues regarding the management and integration of it. Therefore, the search for this knowledge becomes complex and difficult, considering the amount of information in some domains. However, this knowledge shows great importance to experts, who can analyze this information and use it to reach conclusions that are used in decision making or as a way for solving specific problems. Based on these requirements, this dissertation proposes a system to aid classification task, aiming to provide functionalities that allow the expert to maintain domain information in a knowledge base. Also, it is possible to disseminate this information to the others users through searches and/or suggestions, presenting information about the resulting knowledge. The results presented by the system are generated by an inference engine based on Expert Systems, which seeks to produce reasoning from users information about the domain. Along with the inference system is proposed a combination of images related to the knowledge as a way of illustrating the information and descriptions. Also, Image Processing algorithms are employed to reduce subjectivity in cases of uncertainty, regarding the visual characteristics of the case of study, considering the lack of discrete definitions for some information that describe the knowledge. A system was proposed for integrating the Expert Systems and Image Processing techniques. As a way to demonstrate the system applicability, a pertinent problem of paleontology domain focused in classification of Ostracodes species, which have great importance to petroleum exploration, was developed. The system was validated with users and experts that highlight its contribution: able to concentrate and store a big volume of information of many domains, incorporating support decision by image processing, and to be precise to map the expert knowledge. The experts cited as a major contribution that the system represents an application destined to inexperienced users, like students and novice researchers, used in the learning/training process.