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
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Accelerating XPath location steps
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Top.K Frequent Closed Patterns without Minimum Support
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
ICDE '01 Proceedings of the 17th 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
Fast vertical mining using diffsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Algorithms for Mining Closed Itemsets and Their Lattice Structure
IEEE Transactions on Knowledge and Data Engineering
TFP: An Efficient Algorithm for Mining Top-K Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
TSP: Mining top-k closed sequential patterns
Knowledge and Information Systems
Fast Algorithms for Frequent Itemset Mining Using FP-Trees
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Spatio-Temporal Sequential Patterns
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
An Algorithm for In-Core Frequent Itemset Mining on Streaming Data
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
CP-Miner: a tool for finding copy-paste and related bugs in operating system code
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
High-utility pattern mining: A method for discovery of high-utility item sets
Pattern Recognition
VTK: Vertical Mining of Top-Rank-K Frequent Patterns
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
Frequent pattern mining with uncertain data
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Cartesian contour: a concise representation for a collection of frequent sets
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns from network flows for monitoring network
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Mining Top-Rank-k frequent patterns is an emerging topic in frequent pattern mining in recent years. In this paper, we propose a new mining algorithm, NTK, to mining Top-Rank-k frequent patterns. The NTK algorithm employs a data structure, Node-list, to represent patterns. The Node-list structure makes the mining process much efficient. We have experimentally evaluated our algorithm against two representative algorithms on four real datasets. The experimental results show that the NTK algorithm is efficient and is at least two orders of magnitude faster than the FAE algorithm and also remarkably faster than the VTK algorithm, the recently reported state-of-the-art algorithm for mining Top-Rank-k frequent patterns.