Finding Sequential Patterns in Probabilistic Data
- Metanat Hooshsadat
- Samaneh Bayat
- Parisa Naeimi
- Mahdieh S. Mirian
- Osmar R. Zaiane, University of Alberta (Database)
Uncertainty in various domains implies the necessity for data mining techniques and algorithms that can handle uncertain datasets. Many studies on uncertain datasets have focused on modeling, query ranking, discovering frequent patterns, classification models, clustering, etc. However despite the existing need, not many studies have considered uncertainty in sequential data. This paper introduces UAprioriAll, a method to mine frequent sequences in the presence of uncertainty in transactions. UAprioriAll scales linearly in time relative to the size of the dataset.
Citation
M. Hooshsadat, S. Bayat, P. Naeimi, M. Mirian, O. Zaiane. "Finding Sequential Patterns in Probabilistic Data". International FLINS Conference on Uncertainty Modeling in Knowledge Engineering and Decision Making, Istanbul, Turkey, pp 907-912, August 2012.| Keywords: | |
| Category: | In Conference |
BibTeX
@incollection{Hooshsadat+al:FLINS12,
author = {Metanat Hooshsadat and Samaneh Bayat and Parisa Naeimi and Mahdieh
S. Mirian and Osmar R. Zaiane},
title = {Finding Sequential Patterns in Probabilistic Data},
Pages = {907-912},
booktitle = {International FLINS Conference on Uncertainty Modeling in
Knowledge Engineering and Decision Making},
year = 2012,
}Last Updated: January 13, 2020Submitted by Sabina P
