Results 131 to 140 of about 5,295 (219)

Mining high average-utility itemsets

2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
The average utility measure is adopted in this paper to reveal a better utility effect of combining several items than the original utility measure. A mining algorithm is then proposed to efficiently find the high average-utility itemsets. It uses the summation of the maximal utility among the items in each transaction including the target itemset as ...
Tzung-Pei Hong, Cho-Han Lee, Shyue-Liang Wang   +2 more
openaire   +1 more source

High-utility and diverse itemset mining

Applied Intelligence, 2021
High-utility Itemset Mining (HUIM) finds patterns from a transaction database with their utility no less than a user-defined threshold. The utility of an itemset is defined as the sum of the utilities of its items. The utility notion enables a data analyst to associate a profit score with each item and thereof to a pattern. We extend the notion of high-
Amit Verma, Siddharth Dawar, Raman Kumar, Shamkant Navathe, Vikram Goyal   +4 more
openaire   +1 more source

Review on High Utility Itemset Mining Algorithms

Asian Journal of Research in Social Sciences and Humanities, 2016
Finding interesting patterns in the database is an important research area in the field of data mining. Association Rule Mining (ARM) finds the items that go together. It finds out the association between items. Frequent Itemset Mining (FIM) finds out the itemset that occur frequently in the database.
V. Kavitha, B. G. Geetha
openaire   +1 more source

Efficient Incremental High Utility Itemset Mining

Proceedings of the ASE BigData & SocialInformatics 2015, 2015
High-utility itemset mining (HUIM) in transaction databases is an important data mining task with wide applications. However, most HUIM algorithms assume the unrealistic assumption that databases are static. To address this issue, algorithms have been designed to maintain high-utility itemsets in dynamic databases. However, these incremental algorithms
Philippe Fournier-Viger, Jerry Chun-Wei Lin, Ted Gueniche, Prashant Barhate   +3 more
openaire   +1 more source

FPGA-Based Accelerator for Parallel High Utility Itemset Mining Using Utility List

International Conference on Parallel and Distributed Systems
In association rule mining, frequent itemset mining (FIM) optimization is moving from software to hardware acceleration. High utility itemset mining (HUIM), which is an advanced FIM extension, solves traditional FIM's inability to handle highvalue data ...
Gufeng Li, Ying Wu, Zhanpeng Wei, Jiawei Xiang, Tao Shang   +4 more
semanticscholar   +1 more source

Mining High Transaction-Weighted Utility Itemsets

2010 Second International Conference on Computer Engineering and Applications, 2010
In this paper, we design a new kind of patterns, named high transaction-weighted utility itemsets, which considers not only individual profits and quantities of the items in a transaction, but also the contribution of each transaction in a database. We also propose a two-phased mining algorithm to discover high transaction-weighted utility itemsets ...
Guo-Cheng Lan, Tzung-Pei Hong, Vincent S. Tseng   +2 more
openaire   +1 more source

GPU-Based Efficient Parallel Heuristic Algorithm for High-Utility Itemset Mining in Large Transaction Datasets

IEEE Transactions on Knowledge and Data Engineering
Heuristic algorithms have been developed to find approximate solutions for high-utility itemset mining (HUIM) problems that compensate for the performance bottlenecks of exact algorithms.
Wei Fang, Haipeng Jiang, Hengyang Lu, Jun Sun, Xiaojun Wu, Jerry Chun-Wei Lin   +5 more
semanticscholar   +1 more source

Mining summarization of high utility itemsets

Knowledge-Based Systems, 2015
Mining interesting itemsets from transaction databases has attracted a lot of research interests for decades. In recent years, high utility itemset (HUI) has emerged as a hot topic in this field. In real applications, the bottleneck of HUI mining is not at the efficiency but at the interpretability, due to the huge number of itemsets generated by the ...
Xiong Zhang, Zhi-Hong Deng
openaire   +1 more source

Correlated High Average-Utility Itemset Mining

2020
High average-utility itemset (HAUI) mining is an advancement over high utility itemset mining, where average-utility is used instead of utility measure to discover meaningful patterns. It has been discussed in several past studies that significance of utility-based patterns can be amplified if items in the patterns are correlated.
Krishan Kumar Sethi, Dharavath Ramesh
openaire   +1 more source

Efficient closed high-utility itemset mining

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016
This paper presents a novel algorithm for discovering closed high-utility itemsets (CHUIs) efficiently. It proposes three strategies to mine CHUIs efficiently: closure jumping, forward closure checking and backward closure checking. It also relies on two new upper-bounds named local utility and sub-tree utility to prune the search space, and a Fast ...
Philippe Fournier-Viger, Souleymane Zida, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng   +4 more
openaire   +1 more source