Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Turbo-charging vertical mining of large databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Depth first generation of long patterns
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
An efficient approach to discovering knowledge from large databases
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Pincer-Search: An Efficient Algorithm for Discovering the Maximum Frequent Set
IEEE Transactions on Knowledge and Data Engineering
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
SmartMiner: A Depth First Algorithm Guided by Tail Information for Mining Maximal Frequent Itemsets
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Fast Algorithms for Frequent Itemset Mining Using FP-Trees
IEEE Transactions on Knowledge and Data Engineering
Frequent pattern mining: current status and future directions
Data Mining and Knowledge Discovery
Discovery of maximum length frequent itemsets
Information Sciences: an International Journal
Efficient strategies for tough aggregate constraint-based sequential pattern mining
Information Sciences: an International Journal
Discovering frequent itemsets by support approximation and itemset clustering
Data & Knowledge Engineering
An efficient algorithm for mining closed inter-transaction itemsets
Data & Knowledge Engineering
Index-BitTableFI: An improved algorithm for mining frequent itemsets
Knowledge-Based Systems
RETRACTED: Efficient mining of temporal emerging itemsets from data streams
Expert Systems with Applications: An International Journal
IEEE Transactions on Knowledge and Data Engineering
Efficient single-pass frequent pattern mining using a prefix-tree
Information Sciences: an International Journal
TCOM, an innovative data structure for mining association rules among infrequent items
Computers & Mathematics with Applications
Discovering patterns of missing data in survey databases: An application of rough sets
Expert Systems with Applications: An International Journal
IMine: Index Support for Item Set Mining
IEEE Transactions on Knowledge and Data Engineering
An Improved Algorithm for Mining Maximal Frequent Patterns
JCAI '09 Proceedings of the 2009 International Joint Conference on Artificial Intelligence
Data & Knowledge Engineering
Sliding window-based frequent pattern mining over data streams
Information Sciences: an International Journal
An efficient and effective association-rule maintenance algorithm for record modification
Expert Systems with Applications: An International Journal
Soft computing for automated surface quality analysis of exterior car body panels
Applied Soft Computing
Parallel TID-based frequent pattern mining algorithm on a PC Cluster and grid computing system
Expert Systems with Applications: An International Journal
Using data mining techniques to automatically construct concept maps for adaptive learning systems
Expert Systems with Applications: An International Journal
Strategy for mining association rules for web pages based on formal concept analysis
Applied Soft Computing
A new association rules mining algorithms based on directed itemsets graph
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Knowledge-Based Interactive Postmining of Association Rules Using Ontologies
IEEE Transactions on Knowledge and Data Engineering
An efficient algorithm for incremental mining of temporal association rules
Data & Knowledge Engineering
Continuous Subgraph Pattern Search over Certain and Uncertain Graph Streams
IEEE Transactions on Knowledge and Data Engineering
A fast pruning redundant rule method using Galois connection
Applied Soft Computing
Application of particle swarm optimization to association rule mining
Applied Soft Computing
Utility-based association rule mining: A marketing solution for cross-selling
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Mining maximal frequent itemsets is of paramount relevance in many of data mining applications. The ''traditional'' algorithms address this problem through scanning databases many times. The latest research has already focused on reducing the number of scanning times of databases and then decreasing the number of accessing times of I/O resources in order to improve the overall mining efficiency of maximal frequent itemsets of association rules. In this paper, we present a form of the directed itemsets graph to store the information of frequent itemsets of transaction databases, and give the trifurcate linked list storage structure of directed itemsets graph. Furthermore, we develop the mining algorithm of maximal frequent itemsets based on this structure. As a result, one realizes scanning a database only once, and improves storage efficiency of data structure and time efficiency of mining algorithm.