Using Latent Semantic Indexing as a metric for evaluating research potentialities through Innovation Public Policies

Autores

  • Renan Oliveira Silva Universidade Federal do Tocantins
  • Rafael Lima de Carvalho Universidade Federal do Tocantins

DOI:

https://doi.org/10.20873/uft.2675-3588.2021.v2n2.p10-15

Palavras-chave:

Análise por semântica latente, Ciência e Tecnologia, Políticas de Pesquisa e Inovação, Semântica Latente

Resumo

Public innovation policies usually define strategies for Public research organizations, such as universities, in order to guide the next research projects of such organizations. Sometimes, it is difficult to know the actual state of an organization when a new policy is released by the government. The objective of this paper is to present the application of Latent Semantic Analysis, a technique of information retrieval, in order to create an index and automatically classify research projects, using text fields like title and abstract, to areas and subareas defined by related terms. It is also proposed a case study of about 200 projects from five graduate programs of the Universidade Federal do Tocantins. The proposed solution was capable of satisfactorily classify each project to the areas and subareas of a recent policy from the Science, Technology, Innovations, and Communications Ministry. In this way, the university could have some decision-making information, and the results could sustain for which internal policies could be implemented to maximize its actuation faced to the national innovation policy.

Biografia do Autor

Rafael Lima de Carvalho, Universidade Federal do Tocantins

Possui graduação em Ciência da Computação pela Universidade Federal do Tocantins (2006), mestrado em Sistemas e Computação pelo Instituto Militar de Engenharia (2008) e doutorado em Engenharia de Sistemas e Computação pela Universidade Federal do Rio de Janeiro (2016). Atualmente é professor adjunto da Universidade Federal do Tocantins, curso de ciência da computação. Tem experiência na área de Ciência da Computação, com ênfase em Inteligência Computacional, atuando principalmente nos seguintes temas: tracker, weightless neural networks, problema de conectividade dinâmica, aprendizado de máquina.

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Publicado

2021-08-11

Como Citar

[1]
Oliveira Silva, R. e Lima de Carvalho, R. 2021. Using Latent Semantic Indexing as a metric for evaluating research potentialities through Innovation Public Policies. Academic Journal on Computing, Engineering and Applied Mathematics. 2, 2 (ago. 2021), 10–15. DOI:https://doi.org/10.20873/uft.2675-3588.2021.v2n2.p10-15.

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