Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A tree projection algorithm for generation of frequent item sets
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
TBAR: An efficient method for association rule mining in relational databases
Data & Knowledge Engineering
Parametric Algorithms for Mining Share Frequent Itemsets
Journal of Intelligent Information Systems
Data Mining: Concepts, Models, Methods and Algorithms
Data Mining: Concepts, Models, Methods and Algorithms
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Extracting Share Frequent Itemsets with Infrequent Subsets
Data Mining and Knowledge Discovery
Share Based Measures for Itemsets
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining frequent item sets by opportunistic projection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Objective-Oriented Utility-Based Association Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining Association Rules with Weighted Items
IDEAS '98 Proceedings of the 1998 International Symposium on Database Engineering & Applications
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
Fast Algorithms for Frequent Itemset Mining Using FP-Trees
IEEE Transactions on Knowledge and Data Engineering
A fast high utility itemsets mining algorithm
UBDM '05 Proceedings of the 1st international workshop on Utility-based data mining
Perfect Hashing Schemes for Mining Association Rules
The Computer Journal
Mining itemset utilities from transaction databases
Data & Knowledge Engineering - Special issue: ER 2003
Mining weighted association rules
Intelligent Data Analysis
A fast algorithm for mining share-frequent itemsets
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
Direct candidates generation: a novel algorithm for discovering complete share-frequent itemsets
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
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
Mining high utility patterns in incremental databases
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Handling Dynamic Weights in Weighted Frequent Pattern Mining
IEICE - Transactions on Information and Systems
An Efficient Candidate Pruning Technique for High Utility Pattern Mining
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
HHUIF and MSICF: Novel algorithms for privacy preserving utility mining
Expert Systems with Applications: An International Journal
UP-Growth: an efficient algorithm for high utility itemset mining
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
An efficient strategy for mining high utility itemsets
International Journal of Intelligent Information and Database Systems
HUC-Prune: an efficient candidate pruning technique to mine high utility patterns
Applied Intelligence
Mining high utility mobile sequential patterns in mobile commerce environments
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
MHUI-max: An efficient algorithm for discovering high-utility itemsets from data streams
Journal of Information Science
Discovering valuable user behavior patterns in mobile commerce environments
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
An efficient mining algorithm for maximal weighted frequent patterns in transactional databases
Knowledge-Based Systems
Mining social networks for significant friend groups
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications
Interactive mining of high utility patterns over data streams
Expert Systems with Applications: An International Journal
Mining top-K high utility itemsets
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
USpan: an efficient algorithm for mining high utility sequential patterns
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
High utility pattern mining using the maximal itemset property and lexicographic tree structures
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Mining high utility itemsets without candidate generation
Proceedings of the 21st ACM international conference on Information and knowledge management
A tree-based approach for mining frequent weighted utility itemsets
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Mining interesting user behavior patterns in mobile commerce environments
Applied Intelligence
Mining high utility episodes in complex event sequences
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
On-shelf utility mining with negative item values
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Mining high utility itemsets by dynamically pruning the tree structure
Applied Intelligence
UT-Tree: Efficient mining of high utility itemsets from data streams
Intelligent Data Analysis
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Traditional methods of association rule mining consider the appearance of an item in a transaction, whether or not it is purchased, as a binary variable. However, customers may purchase more than one of the same item, and the unit cost may vary among items. Utility mining, a generalized form of the share mining model, attempts to overcome this problem. Since the Apriori pruning strategy cannot identify high utility itemsets, developing an efficient algorithm is crucial for utility mining. This study proposes the Isolated Items Discarding Strategy (IIDS), which can be applied to any existing level-wise utility mining method to reduce candidates and to improve performance. The most efficient known models for share mining are ShFSM and DCG, which also work adequately for utility mining as well. By applying IIDS to ShFSM and DCG, the two methods FUM and DCG+ were implemented, respectively. For both synthetic and real datasets, experimental results reveal that the performance of FUM and DCG+ is more efficient than that of ShFSM and DCG, respectively. Therefore, IIDS is an effective strategy for utility mining.