Abstract

Literature reviews are a crucial but time-consuming and complex task in scientific research. As such, interest in automating this process using machine learning techniques has increased over the last few years. In this paper, we present a method of streamlining the process of writing literature reviews by automating several aspects of the process using Maestro v2023, an automatic and flexible data gathering and classification platform. Maestro v2023 is a revamped version of the original Maestro platform, designed to be modular and configurable, allowing users in an organization to create search contexts that automatically gather and classify data for them. We analyze the work related to literature review automation and suggest how Maestro can contribute to this field, demonstrating how the system was utilized in order to streamline our own literature review process, as well aid us in formulating the abstract and extracting relevant keywords to this paper.

Recommended Citation

Martins, A.M., Rodrigues da Silva, A., & Estima, J. (2023). Streamlining Literature Reviews Using an Automatic and Flexible Data Gathering and Classification Platform. In A. R. da Silva, M. M. da Silva, J. Estima, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development, Organizational Aspects and Societal Trends (ISD2023 Proceedings). Lisbon, Portugal: Instituto Superior Técnico. ISBN: 978-989-33-5509-1. https://doi.org/10.62036/ISD.2023.53

Paper Type

Short Paper

DOI

10.62036/ISD.2023.53

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Streamlining Literature Reviews Using an Automatic and Flexible Data Gathering and Classification Platform

Literature reviews are a crucial but time-consuming and complex task in scientific research. As such, interest in automating this process using machine learning techniques has increased over the last few years. In this paper, we present a method of streamlining the process of writing literature reviews by automating several aspects of the process using Maestro v2023, an automatic and flexible data gathering and classification platform. Maestro v2023 is a revamped version of the original Maestro platform, designed to be modular and configurable, allowing users in an organization to create search contexts that automatically gather and classify data for them. We analyze the work related to literature review automation and suggest how Maestro can contribute to this field, demonstrating how the system was utilized in order to streamline our own literature review process, as well aid us in formulating the abstract and extracting relevant keywords to this paper.