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 Priscila Rodrigues(priscila.rfr@alu.ufc.com)
2 Ticiana da Silva(ticianalc@ufc.br)
3 Flávio Sousa(sousa@ufc.br)
4 Regis Magalhães(regismagalhaes@ufc.br)
5 José Macêdo(jose.macedo@lia.ufc.br)

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

Reference
# Reference
1 Ester, Martin et al. A density-based algorithm for discovering clusters in large spatial databases with noise. In: Kdd. 1996. p. 226-231.
2 Jain, Anil K.; Murty, M. Narasimha; Flynn, Patrick J. Data clustering: a review. ACM computing surveys (CSUR), v.31, n. 3, p. 264-323, 1999.
3 Kaur, S. et al. Concept drift in unlabeled data stream. Technical Report, University of Delhi, 2009
4 Kim, Min-Soo; Han, Jiawei. A particle-and-density based evolutionary clustering method for dynamic networks. Proceedings of the VLDB Endowment, v. 2, n. 1, p. 622-633, 2009.
5 Lee, Pei et al. Incremental cluster evolution tracking from highly dynamic network data.In: Data Engineering (ICDE). IEEE, 2014. p. 3-14.
6 Coelho da Silva, Ticiana L., José AF de Macêdo, and Marco A. Casanova. "Discovering frequent mobility patterns on moving object data. "Proceedings of the Third ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems. ACM, 2014.
7 Spiliopoulou, Myra et al. Monic: modeling and monitoring cluster transitions. In: Proceedingsof the 12th ACM SIGKDD. ACM, 2006. p. 706-711.
8 Tang, Lu-An et al. A framework of traveling companion discovery on trajectory data streams. ACM Transactions on Intelligent Systems and Technology (TIST), v. 5, n. 1, p. 3, 2013.