Mining Frequent Itemsets from Uncertain Data
By C. Chui, B. Kao, Edward C. K. Hung. Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2007
411 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/6995cc1b180cfc51a5759ef07af3414b02d1dd3c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Philip S. Yu
- Charu C. Aggarwal
- Hans-Peter Kriegel
- Jiawei Han
- Mohammed J. Zaki
- Johannes Gehrke
- Wenliang Du
- Yizhou Sun
In Information Systems
- Charu C. Aggarwal
- Philip S. Yu
- Hans-Peter Kriegel
- Jiawei Han
- Yongfeng Zhang
- Mohammed J. Zaki
- B. Liu
- George Karypis
In Signal Processing
- Charu C. Aggarwal
- Philip S. Yu
- Hans-Peter Kriegel
- Jiawei Han
- Arthur Zimek
- Pavel Berkhin
- Aleksandar Lazarevic
- Peer Kröger
Citations in the corpus
- Probabilistic frequent itemset mining in uncertain databases (2009, methodology): “al [6] computes the expected support of itemsets by summing all itemset probabilities in their U-Apriori algorithm.”
- A Survey of Uncertain Data Algorithms and Applications (2009, background): “In [29], it has been shown that this approach can accurately mine the frequent patterns while maintaining efficiency.”