Turbo-charging vertical mining of large databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
On the Discovery of Interesting Patterns in Association Rules
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Carpenter: finding closed patterns in long biological datasets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
COBBLER: Combining Column and Row Enumeration for Closed Pattern Discovery
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Mining coherent gene clusters from gene-sample-time microarray data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
TRICLUSTER: an effective algorithm for mining coherent clusters in 3D microarray data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Closed patterns meet n-ary relations
ACM Transactions on Knowledge Discovery from Data (TKDD)
What Can Formal Concept Analysis Do for Data Warehouses?
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Multi-way set enumeration in real-valued tensors
Proceedings of the 2nd Workshop on Data Mining using Matrices and Tensors
Closed Non Derivable Data Cubes Based on Non Derivable Minimal Generators
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Discovering Relevant Cross-Graph Cliques in Dynamic Networks
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Actionability and formal concepts: a data mining perspective
ICFCA'08 Proceedings of the 6th international conference on Formal concept analysis
A case study on financial ratios via cross-graph quasi-bicliques
Information Sciences: an International Journal
Mining triadic association rules from ternary relations
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
From triconcepts to triclusters
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Scalable mining of frequent tri-concepts from folksonomies
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
A survey on enhanced subspace clustering
Data Mining and Knowledge Discovery
Closed and noise-tolerant patterns in n-ary relations
Data Mining and Knowledge Discovery
Review: Formal Concept Analysis in knowledge processing: A survey on models and techniques
Expert Systems with Applications: An International Journal
Interesting pattern mining in multi-relational data
Data Mining and Knowledge Discovery
Discovering descriptive rules in relational dynamic graphs
Intelligent Data Analysis - Dynamic Networks and Knowledge Discovery
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In this paper, we introduce the concept of frequent closed cube (FCC), which generalizes the notion of 2D frequent closed pattern to 3D context. We propose two novel algorithms to mine FCCs from 3D datasets. The first scheme is a Representative Slice Mining (RSM) framework that can be used to extend existing 2D FCP mining algorithms for FCC mining. The second technique, called CubeMiner, is a novel algorithm that operates on the 3D space directly. We have implemented both schemes, and evaluated their performance on both real and synthetic datasets. The experimental results show that the RSM-based scheme is efficient when one of the dimensions is small, while CubeMiner is superior otherwise.