Use of text mining techniques for unsupervised organization of digital procedural acts

Abstract

The rapid advances in technologies related to the capture and storage of data in digital format have allowed to organizations the accumulation of a volume of information extremely high, constituted a higher proportion of data in unstructured format, represented by texts. However, it is noted that the retrieval of useful information from these large repositories has been a very challenging activity. In this context, data mining is presented as a self-discovery process that acts on large databases and enables the knowledge extraction from raw text documents. Among the many sources of textual documents are electronic diaries of justice, which are intended to make public officially all the acts of the Judiciary. Despite the publication in digital form has provided improvements represented by the removal of imperfections related to divulgation at printed format, it is observed that the application of data mining methods could render more rapid analysis of its contents. In this sense, this article establishes a tool capable of automatically grouping and categorizing digital procedural acts, based on the evaluation of text mining techniques applied to groups determination activity. In addition, the strategy of defining the descriptors of the groups, that is usually conducted based on the most frequent words in the documents, was evaluated and remodeled in order to use, instead of words, the most regularly identified concepts in the texts.