eMailMe: A Method to Build Datasets of Corporate Emails in Portuguese

Akira A. de Moura Galvão Uematsu () and Anarosa A. F. Brandão
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Akira A. de Moura Galvão Uematsu: Engenharia de Computação e Sistemas Digitais, Escola Politécnica-Universidade de São Paulo, Av. Prof. Luciano Gualberto, São Paulo 05508-010, Brazil
Anarosa A. F. Brandão: Engenharia de Computação e Sistemas Digitais, Escola Politécnica-Universidade de São Paulo, Av. Prof. Luciano Gualberto, São Paulo 05508-010, Brazil

Data, 2023, vol. 8, issue 8, 1-12

Abstract: One of the areas in which knowledge management has application is in companies that are concerned with maintaining and disseminating their practices among their members. However, studies involving these two domains may end up suffering from the issue of data confidentiality. Furthermore, it is difficult to find data regarding organizations processes and associated knowledge. Therefore, this paper presents a method to support the generation of a labeled dataset composed of texts that simulate corporate emails containing sensitive information regarding disclosure, written in Portuguese. The method begins with the definition of the dataset’s size and content distribution; the structure of its emails’ texts; and the guidelines for specialists to build the emails’ texts. It aims to create datasets that can be used in the validation of a tacit knowledge extraction process considering the 5W1H approach for the resulting base. The method was applied to create a dataset with content related to several domains, such as Federal Court and Registry Office and Marketing, giving it diversity and realism, while simulating real-world situations in the specialists’ professional life. The dataset generated is available in an open-access repository so that it can be downloaded and, eventually, expanded.

Keywords: knowledge management; knowledge acquisition; tacit knowledge; 5W1H; natural language processing (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2023
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