Knowledge extraction using visualization of hemoglobin parameters to identify thalassemia

The analysis of large amounts of data is better performed by humans when represented in a graphical format. Therefore, a new research area called the Visual Data Mining is being developed endeavoring to use the number crunching power of computers to prepare data for visualization, allied to the ability of humans to interpret data presented graphically.This work presents the results of applying a visual data mining tool, called FastMapDB to detect the behavioral pattern exhibited by a dataset of clinical information about hemoglobinopathies known as thalassemia. FastMapDB is a visual data mining tool that get tabular data stored in a relational database such as dates, numbers and texts, and by considering them as points in a multidimensional space, maps them to a three-dimensional space. The intuitive three-dimensional representation of objects enables a data analyst to see the behavior of the characteristics from abnormal forms of hemoglobin, highlighting the differences when compared to data from a group without alteration.

Automatic Indexing and Information Visualization: A Study Based on Paraconsistent Logic

This paper reports a research to evaluate the potential and the effects of use of annotated Paraconsistent logic in automatic indexing. This logic attempts to deal with contradictions, concerned with studying and developing inconsistency-tolerant systems of logic. This logic, being flexible and containing logical states that go beyond the dichotomies yes and no, permits to advance the hypothesis that the results of indexing could be better than those obtained by traditional methods. Interactions between different disciplines, as information retrieval, automatic indexing, information visualization, and nonclassical logics were considered in this research. From the methodological point of view, an algorithm for treatment of uncertainty and imprecision, developed under the Paraconsistent logic, was used to modify the values of the weights assigned to indexing terms of the text collections. The tests were performed on an information visualization system named Projection Explorer (PEx), created at Institute of Mathematics and Computer Science (ICMC - USP Sao Carlos), with available source code. PEx uses traditional vector space model to represent documents of a collection. The results were evaluated by criteria built in the information visualization system itself, and demonstrated measurable gains in the quality of the displays, confirming the hypothesis that the use of the para-analyser under the conditions of the experiment has the ability to generate more effective clusters of similar documents. This is a point that draws attention, since the constitution of more significant clusters can be used to enhance information indexing and retrieval. It can be argued that the adoption of non-dichotomous (non-exclusive) parameters provides new possibilities to relate similar information.