Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Scoring the Data Using Association Rules
Applied Intelligence
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Association Analysis with One Scan of Databases
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Weighted Association Rule Mining using weighted support and significance framework
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
WAR: Weighted Association Rules for Item Intensities
Knowledge and Information Systems
estWin: Online data stream mining of recent frequent itemsets by sliding window method
Journal of Information Science
Fast Algorithms for Frequent Itemset Mining Using FP-Trees
IEEE Transactions on Knowledge and Data Engineering
Data Mining and Knowledge Discovery
An integrated efficient solution for computing frequent and top-k elements in data streams
ACM Transactions on Database Systems (TODS)
DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Mining lossless closed frequent patterns with weight constraints
Knowledge-Based Systems
Towards a new approach for mining frequent itemsets on data stream
Journal of Intelligent Information Systems
Mining itemset utilities from transaction databases
Data & Knowledge Engineering - Special issue: ER 2003
CanTree: a canonical-order tree for incremental frequent-pattern mining
Knowledge and Information Systems
EDUA: An efficient algorithm for dynamic database mining
Information Sciences: an International Journal
Efficient mining of weighted interesting patterns with a strong weight and/or support affinity
Information Sciences: an International Journal
Frequent pattern mining: current status and future directions
Data Mining and Knowledge Discovery
Incremental and interactive mining of web traversal patterns
Information Sciences: an International Journal
CTU-Mine: An Efficient High Utility Itemset Mining Algorithm Using the Pattern Growth Approach
CIT '07 Proceedings of the 7th IEEE International Conference on Computer and Information Technology
Isolated items discarding strategy for discovering high utility itemsets
Data & Knowledge Engineering
An efficient algorithm for mining temporal high utility itemsets from data streams
Journal of Systems and Software
A survey on algorithms for mining frequent itemsets over data streams
Knowledge and Information Systems
Online mining of frequent sets in data streams with error guarantee
Knowledge and Information Systems
Updating generalized association rules with evolving taxonomies
Applied Intelligence
DSM-FI: an efficient algorithm for mining frequent itemsets in data streams
Knowledge and Information Systems
Efficient frequent pattern mining over data streams
Proceedings of the 17th ACM conference on Information and knowledge management
Efficient single-pass frequent pattern mining using a prefix-tree
Information Sciences: an International Journal
Fast and Memory Efficient Mining of High Utility Itemsets in Data Streams
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Finding Frequent Closed Itemsets in Sliding Window in Linear Time
IEICE - Transactions on Information and Systems
DRFP-tree: disk-resident frequent pattern tree
Applied Intelligence
Efficient Tree Structures for High Utility Pattern Mining in Incremental Databases
IEEE Transactions on Knowledge and Data Engineering
Knowledge and Information Systems - Special Issue on Data Warehousing and Knowledge Discovery from Sensors and Streams
A fast algorithm for maintenance of association rules in incremental databases
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
A two-phase algorithm for fast discovery of high utility itemsets
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Efficient frequent pattern mining based on Linear Prefix tree
Knowledge-Based Systems
| Hi-index | 12.05 |
High utility pattern (HUP) mining over data streams has become a challenging research issue in data mining. When a data stream flows through, the old information may not be interesting in the current time period. Therefore, incremental HUP mining is necessary over data streams. Even though some methods have been proposed to discover recent HUPs by using a sliding window, they suffer from the level-wise candidate generation-and-test problem. Hence, they need a large amount of execution time and memory. Moreover, their data structures are not suitable for interactive mining. To solve these problems of the existing algorithms, in this paper, we propose a novel tree structure, called HUS-tree (high utility stream tree) and a new algorithm, called HUPMS (high utility pattern mining over stream data) for incremental and interactive HUP mining over data streams with a sliding window. By capturing the important information of stream data into an HUS-tree, our HUPMS algorithm can mine all the HUPs in the current window with a pattern growth approach. Furthermore, HUS-tree is very efficient for interactive mining. Extensive performance analyses show that our algorithm is very efficient for incremental and interactive HUP mining over data streams and significantly outperforms the existing sliding window-based HUP mining algorithms.