This article describes the results of a research applying Knowledge Discovery in Texts (KDT) in textual contents, which are important sources of information for decision-making purposes. The main objective of the research is to verify the effectiveness of KDT for discovering information that may support the construction of ST&I indicators and for the definition of public policies. The case study of the research was the textual content of the Brazilian Service for Technical Answers (Serviço Brasileiro de Respostas Técnicas - SBRT) and the technique adopted was document clustering from terms mined in the database. The use of DCT for extracting hidden information - that could not be found by using the traditional information retrieval - from textual documents proved to be efficient. The presence of environmental concerns in the demand posted by SBRT's users and the applicability of DCT to orient internal policies for SBRT network were also evidenced by the research results.
Knowledge Discovery in Texts (KDT); Text mining; S&T indicators; Information services; Micro-enterprises; Entrepreneurs
