FpViz: a visualizer for frequent pattern mining
Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration
Efficient algorithms for mining constrained frequent patterns from uncertain data
Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data
Mining uncertain data for constrained frequent sets
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Mining uncertain data for frequent itemsets that satisfy aggregate constraints
Proceedings of the 2010 ACM Symposium on Applied Computing
FpVAT: a visual analytic tool for supporting frequent pattern mining
ACM SIGKDD Explorations Newsletter
Efficient algorithms for the mining of constrained frequent patterns from uncertain data
ACM SIGKDD Explorations Newsletter
Increasing availability of industrial systems through data stream mining
Computers and Industrial Engineering
Frequent itemset mining of uncertain data streams using the damped window model
Proceedings of the 2011 ACM Symposium on Applied Computing
Frequent pattern mining from time-fading streams of uncertain data
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
A practice probability frequent pattern mining method over transactional uncertain data streams
UIC'11 Proceedings of the 8th international conference on Ubiquitous intelligence and computing
Mining frequent patterns from univariate uncertain data
Data & Knowledge Engineering
Distributed mining of constrained frequent sets from uncertain data
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
A landmark-model based system for mining frequent patterns from uncertain data streams
Proceedings of the 15th Symposium on International Database Engineering & Applications
Fast tree-based mining of frequent itemsets from uncertain data
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
Mining probabilistic datasets vertically
Proceedings of the 16th International Database Engineering & Applications Sysmposium
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Mining popular patterns from transactional databases
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Mining frequent subgraphs over uncertain graph databases under probabilistic semantics
The VLDB Journal — The International Journal on Very Large Data Bases
Constrained frequent pattern mining on univariate uncertain data
Journal of Systems and Software
Stream mining of frequent sets with limited memory
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Stream mining on univariate uncertain data
Applied Intelligence
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Frequent itemset mining plays an essential role in the mining of various patterns and is in demand in many real-life applications. Hence, mining of frequent itemsets has been the subject of numerous studies since its introduction. Generally, most of these studies find frequent itemsets from traditional transaction databases, in which the content of each transaction--namely, items--is definitely known and precise. However, there are many real-life situations in which ones are uncertain about the content of transactions. This calls for the mining of uncertain data. Moreover, due to advances in technology, a flood of precise or uncertain data can be produced in many situations. This calls for the mining of data streams. To deal with these situations, we propose two tree-based mining algorithms to efficiently find frequent itemsets from streams of uncertain data, where each item in the transactions in the streams is associated with an existential probability. Experimental results show the effectiveness of our algorithms in mining frequent itemsets from streams of uncertain data.