Palla Likhitha, Rage Veena, Rage Uday Kiran, Koji Zettsu, Masashi Toyoda, Philippe Fournier-Viger. UPFP-growth++: An Efficient Algorithm to Find Periodic-Frequent Patterns in Uncertain Temporal Databases. In Mohammad Tanveer 0001, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt, editors, Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part V. Volume 1792 of Communications in Computer and Information Science, pages 182-194, Springer, 2022. [doi]
@inproceedings{LikhithaVKZTF22,
title = {UPFP-growth++: An Efficient Algorithm to Find Periodic-Frequent Patterns in Uncertain Temporal Databases},
author = {Palla Likhitha and Rage Veena and Rage Uday Kiran and Koji Zettsu and Masashi Toyoda and Philippe Fournier-Viger},
year = {2022},
doi = {10.1007/978-981-99-1642-9_16},
url = {https://doi.org/10.1007/978-981-99-1642-9_16},
researchr = {https://researchr.org/publication/LikhithaVKZTF22},
cites = {0},
citedby = {0},
pages = {182-194},
booktitle = {Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part V},
editor = {Mohammad Tanveer 0001 and Sonali Agarwal and Seiichi Ozawa and Asif Ekbal and Adam Jatowt},
volume = {1792},
series = {Communications in Computer and Information Science},
publisher = {Springer},
isbn = {978-981-99-1642-9},
}