R Package: GSTSM – Generalized Spatial-Time Sequence Miner

Student: Rebecca Pontes Salles (rebeccapsalles@acm.org)

Advisor: Eduardo Ogasawara (eogasawara@ieee.org)

Description: Implementations of the algorithms present in the future article Generalized Discovery of Tight Space-Time Sequences.

Available at CRAN: https://cran.r-project.org/web/packages/gstsm/index.html

Code repository at Git-Hub: https://github.com/cefet-rj-dal/gstsm

Reference manual: GSTSM.pdf

Acknowledgments: The authors thank CAPES, FAPERJ, and CNPq for partially sponsoring this work.

Eduardo Ogasawara

I am a Professor of the Computer Science Department of the Federal Center for Technological Education of Rio de Janeiro (CEFET / RJ) since 2010. I hold a PhD in Systems Engineering and Computer Science at COPPE / UFRJ. Between 2000 and 2007 I worked in the Information Technology (IT) field where I acquired extensive experience in workflows and project management. I have solid background in the Databases and my primary interest is Data Science. He currently studies space-time series, parallel and distributed processing, and data preprocessing methods. I am a member of the IEEE, ACM, INNS, and SBC. Throughout my career I have been presenting consistent number of published articles and projects approved by the funding agencies, such as CNPq and FAPERJ. I am also reviewer of several international journals, such as VLDB Journal, IEEE Transactions on Service Computing and The Journal of Systems and Software. Currently, I am heading the Post-Graduate Program in Computer Science (PPCIC) of CEFET / RJ.