Results 71 to 80 of about 5,295 (219)

ASCF: Optimization of the Apriori Algorithm Using Spark‐Based Cuckoo Filter Structure

International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.
Data mining is the process used for extracting hidden patterns from large databases using a variety of techniques. For example, in supermarkets, we can discover the items that are often purchased together and that are hidden within the data. This helps make better decisions which improve the business outcomes.
Bana Ahmad Alrahwan, Mona Farouk, Yu-an Tan   +2 more
wiley   +1 more source

Selective Database Projections Based Approach for Mining High-Utility Itemsets

IEEE Access, 2018
High-utility itemset mining (HilIM) is an emerging area of data mining and is widely used. HilIM differs from the frequent itemset mining (FIM), as the latter considers only the frequency factor, whereas the former has been designed to address both ...
Anita Bai, Parag S. Deshpande, Meera Dhabu   +2 more
doaj   +1 more source

Mining High-Efficiency Itemsets with Negative Utilities

Mathematics
High-efficiency itemset mining has recently emerged as a new problem in itemset mining. An itemset is classified as a high-efficiency itemset if its utility-to-investment ratio meets or exceeds a specified efficiency threshold.
Irfan Yildirim
doaj   +1 more source

MEMU: More Efficient Algorithm to Mine High Average-Utility Patterns With Multiple Minimum Average-Utility Thresholds

IEEE Access, 2018
High average-utility itemsets mining (HAUIM) is an emerging topic in data mining. Compared to traditional high utility itemset mining, HAUIM more fairly measures the utility of itemsets by considering their lengths (number of items).
Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger   +2 more
doaj   +1 more source

An Efficient Algorithm for Mining Top-k High-On-Shelf-Utility Itemsets with Positive/Negative Profits of Local/Global Minimum Count

Engineering Proceedings
High-utility itemset mining (HUIM) utilizes the threshold value to extract HUI from the transactional database. However, it is difficult to define an optimal threshold value, since it depends on the domain knowledge of the application.
Ye-In Chang, Po-Chun Chuang, Yu-Hao Liao, Po-Yu Hu, Ting-Wei Chen   +4 more
doaj   +1 more source

AN EFFICIENT ALGORITHM FOR MINING HIGH UTILITY ITEMSETS

Tạp chí Khoa học
High utility itemsets (HUIs) mining is the finding of itemsets that satisfy a user-defined minimum utility threshold. Many successful studies in this field have been carried out, however they are all reliant on Tidset techniques, which records the ...
Nguyen Thi Thanh Thuy*, Nguyen Van Le, Manh Thien Ly
doaj   +1 more source

A Pattern-Based Academic Reviewer Recommendation Combining Author-Paper and Diversity Metrics

IEEE Access, 2019
With the rapid increase of publishable research articles and manuscripts, the pressure to find reviewers often overwhelms the journal editors. This paper incorporates the major entity level metrics found in the heterogeneous publication networks into a ...
Musa Ibrahim Musa Ishag, Kwang Ho Park, Jong Yun Lee, Keun Ho Ryu   +3 more
doaj   +1 more source

Mining High Utility Itemsets Using Bio-Inspired Algorithms: A Diverse Optimal Value Framework

IEEE Access, 2018
Mining high utility itemsets (HUI) is an interesting research problem in the field of data mining and knowledge discovery. Recently, bio-inspired computing has attracted considerable attention, leading to the development of new algorithms for mining HUIs.
Wei Song, Chaomin Huang
doaj   +1 more source

Mining actionable combined high utility incremental and associated sequential patterns. [PDF]

PLoS One, 2023
Shi M, Gong Y, Xu T, Zhao L.
europepmc   +1 more source

High Utility Itemset Mining Using Transaction Utility of Itemsets

KIPS Transactions on Software and Data Engineering, 2015
Serin Lee, Jong Soo Park
openaire   +2 more sources