Temporal Evolution of Complex Data

  • Isis Caroline Oliveira de Sousa Fogaça Universidade Federal de São Carlos
  • Renato Bueno Universidade Federal de São Carlos


Monitoring the temporal evolution of data is essential in many areas of application of databases, such as medicine, agriculture and meteorology. Complex data are usually represented in metric spaces, where only the elements and the distances between them are available, which makes it impossible to represent trajectories considering a temporal dimension. In this paper we propose to map the metric data to multidimensional spaces so that we can estimate the element's status at a given time, based on known states of the same element. As it is not possible to create the complex data equivalent to its estimated position, we propose to apply similarity queries using this position as query center. We evaluated three types of similarity queries: k-NN, kAndRange and kAndRev.

Palavras-chave: Temporal databases, complex data, similarity queries


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FOGAÇA, Isis Caroline Oliveira de Sousa; BUENO, Renato. Temporal Evolution of Complex Data. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 35. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 25-36. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2020.13622.