SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Eleonilia Rodrigues(eleoniliamonteiro@copin.ufcg.edu.br)
2 Carlos Eduardo Pires(cesp@dsc.ufcg.edu.br)
3 Dimas Nascimento(dimas.cassimiro@ufape.edu.br)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 [Abdelhédi et al. 2022] Abdelhédi, F., Rajhi, H., and Zurfluh, G. (2022). Extraction process of the logical schema of a document-oriented nosql database. In Proceedings of the 10th International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2022), pages 61–71.
2 [Amorim et al. 2022] Amorim, A., Murrugarra-Llerena, N., Silva, V., de Oliveira, D., and Paes, A. (2022). Modelagem de tópicos em textos curtos: uma avaliação experimental. In Anais do XXXVII Simpósio Brasileiro de Bancos de Dados, pages 254–266, Porto Alegre, RS, Brasil. SBC.
3 [Atmatzides et al. 2022] Atmatzides, N., Bedo, M., and de Oliveira, D. (2022). Adoção de sgbds nosql em empresas brasileiras: um levantamento preliminar. In Anais do XXXVII Simpósio Brasileiro de Bancos de Dados, pages 385–390, Porto Alegre, RS, Brasil. SBC.
4 [Baazizi et al. 2019] Baazizi, M.-A., Colazzo, D., Ghelli, G., and Sartiani, C. (2019). Parametric schema inference for massive json datasets. The VLDB Journal, 28:497–521.
5 [Cánovas Izquierdo and Cabot 2013] Cánovas Izquierdo, J. L. and Cabot, J. (2013). Discovering implicit schemas in json data. In Web Engineering: 13th International Conference, ICWE 2013, Aalborg, Denmark, July 8-12, 2013. Proceedings 13, pages 68–83. Springer.
6 [Foundation 2024] Foundation, P. S. (2024). Deepdiff: Deep difference and search of any python object/data. recreate objects by adding deltas to each other. Accessed: 2024- 07-26.
7 [Frozza et al. 2018] Frozza, A. A., dos Santos Mello, R., and da Costa, F. d. S. (2018). An approach for schema extraction of json and extended json document collections. In IEEE International Conference on Information Reuse and Integration (IRI), pages 356–363.
8 [Hashem and Ranc 2016] Hashem, H. and Ranc, D. (2016). Evaluating nosql document oriented data model. In 2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), pages 51–56.
9 [Izquierdo and Cabot 2016] Izquierdo, J. L. C. and Cabot, J. (2016). Jsondiscoverer: Visualizing the schema lurking behind json documents. Knowledge-Based Systems, 103:52– 55.
10 [Klettke et al. 2017] Klettke, M., Awolin, H., Störl, U., Müller, D., and Scherzinger, S. (2017). Uncovering the evolution history of data lakes. In 2017 IEEE international conference on big data (Big Data), pages 2462–2471. IEEE.
11 [Latták and Koupil 2022] Latták, I. V. and Koupil, P. (2022). A comparative analysis of json schema inference algorithms. In Proceedings of the 17th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2022), pages 379– 386.
12 [Li et al. 2023] Li, X., Sun, L., Ling, M., and Peng, Y. (2023). A survey of graph neural network based recommendation in social networks. Neurocomputing, 549:126441.
13 [Phillips 2016] Phillips, J. (2016). Ecommerce analytics: analyze and improve the impact of your digital strategy. FT Press.
14 [Purnomo 2023] Purnomo, Y. J. (2023). Digital marketing strategy to increase sales conversion on e-commerce platforms. Journal of Contemporary Administration and Management (ADMAN), 1(2):54–62.
15 [Sevilla Ruiz et al. 2015] Sevilla Ruiz, D., Morales, S. F., and García Molina, J. (2015). Inferring versioned schemas from nosql databases and its applications. In Conceptual Modeling: 34th International Conference, ER 2015, Stockholm, Sweden, October 19- 22, 2015, Proceedings 34, pages 467–480. Springer.