Results 71 to 80 of about 719,228 (260)
A SURVEY ON ITEMSET MINING FOR LARGE TRANSACTION DATABASE
, 2016 Mining itemsets from the databases is an important data mining task.Frequent itemset mining refers to the mining of set of items occur frequently in the database.Utility itemset mining refers to the discovery of items with high utilities.
Ancy Jose*, Dr. John T Abraham
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High Voltage, Volume 10, Issue 3, Page 710-725, June 2025.Abstract Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer, thereby facilitating the formulation of power outage maintenance plans and power dispatch strategies. However, existing prediction methods based on the structure of ‘splicing prediction and diagnosis method’ suffer ...
Peng Zhang +5 more
wiley +1 more source
Health Science Reports, Volume 8, Issue 1, January 2025.ABSTRACT Background and Aims Infertility, as defined by the World Health Organization, is the inability to conceive after 12 months of regular, unprotected intercourse. This study aimed to identify factors influencing infertility by applying data mining techniques, specifically rule‐mining methods, to analyze diverse patient data and uncover relevant ...
Hosna Heydarian +3 more
wiley +1 more source
PaWI: Parallel Weighted Itemset Mining by means of MapReduce [PDF]
, 2015 Frequent itemset mining is an exploratory data mining technique that has fruitfully been exploited to extract recurrent co-occurrences between data items.
Luigi Grimaudo +7 more
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IET Communications, Volume 19, Issue 1, January/December 2025.This paper proposed an Automated Quality Assessment of SRS (AQA‐SRS) framework by integrating four popular methods which are; NLP, K‐means, MAS, and CBR to assess the quality of SRS documents. The NLP utilize for feature extraction, K‐means for features clustering, MAS for interactive assessment and feature selection decision, and CBR for managing the ...
Mohammed Ahmed Jubair +6 more
wiley +1 more source
LUIM: New Low-Utility Itemset Mining Framework
IEEE Access, 2019 High-utility itemset mining (HUIM), which is the detection of high-utility itemsets (HUIs) in a transactional database, provides the decision maker with greater flexibility to exploit item utilities, such as quantity and profits, to extract remarkable ...
Naji Alhusaini +5 more
doaj +1 more source
Erasable Itemset Mining for Sequential Product Databases
, 2022 Data mining has become a popular research field in recent years. It is a crucial task to find meaningful information from large databases due to the current progress in networks and storage technology. There are various data mining tasks.
Chen, Yi-Li
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A Java Library for Itemset Mining with Choco-solver
, 2023 While traditional data mining techniques have been used extensively for discovering patterns in databases, they are not always suitable for incorporating user-specified constraints.
Loudni, Samir, Vernerey, Charles
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An AI knowledge‐based system for police assistance in crime investigation
Expert Systems, Volume 42, Issue 1, January 2025.Abstract The fight against crime is often an arduous task overall when huge amounts of data have to be inspected, as is currently the case when it comes for example in the detection of criminal activity on the dark web. This work presents and describes an artificial intelligence (AI) based system that combines various tools to assist police or law ...
Carlos Fernandez‐Basso +4 more
wiley +1 more source
TT-Miner: Topology-Transaction Miner for Mining Closed Itemset
IEEE Access, 2019 Mining frequent closed itemsets (FCIs) from transaction databases is a fundamental problem in many data mining applications. All the enumeration algorithms enumerate FCIs by adding a singleton item to an itemset and then checking whether it is closure ...
Bo Li +3 more
doaj +1 more source