Results 111 to 120 of about 2,506 (215)
Jurnal Informatika, 2007 Taking attendance from employees always becomes a problem for Human Resource Department (HRD) in many companies lately. Although there is an automatic check-lock machine, it still has a weakness.
Gregorius Satia Budhi +1 more
doaj
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
, 2008 In order to generate synthetic basket datasets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket datasets.
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Algoritma Apriori untuk Pencarian Frequent itemset dalam Association Rule Mining
, 2019 Over decades, retail chains and department stores have been selling their products without using the transactional data generated by their sales as a source of knowledge.
Dari, Wulan, Prahartiwi, Lusa Indah
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Impacts of frequent itemset hiding algorithms on privacy preserving data mining [PDF]
, 2010 Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2010Includes bibliographical references (leaves: 54-58)Text in English; Abstract: Turkish and Englishx, 69 leavesThe invincible growing of computer capabilities and collection ...
Yıldız, Barış
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Peringkasan Review Konsumen Restoran Menggunakan Weighted Frequent Itemset Mining [PDF]
, 2019 Review yang dilakukan konsumen terhadap restoran dapat bermanfaat bagi para calon konsumen atau para pemilik restoran untuk mengetahui pendapat orang lain mengenai restoran tersebut.
Yusron, Moh. Iqbal
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Application of K-means supported by clustered systems in big data association rule mining
Systems and Soft Computings: Association rule mining plays an important role in the field of data mining, which is used to discover hidden relationships. However, as data volumes increase, traditional association rule mining methods are constrained to single-machine computing ...
Lihua Liu
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DIAFM: An Improved and Novel Approach for Incremental Frequent Itemset Mining
MathematicsTraditional approaches to data mining are generally designed for small, centralized, and static datasets. However, when a dataset grows at an enormous rate, the algorithms become infeasible in terms of huge consumption of computational and I/O resources.
Mohsin Shaikh +4 more
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Frequent itemset mining using graph theory / Mohammad Arsyad Mohd Yakop [PDF]
, 2017 There is a number of algorithms focusing on frequent itemsets mining (FIM) field, however, some of the problems still require attention, particularly when the mining process involves a high dimensional dataset.
Mohd Yakop, Mohammad Arsyad
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Comparative Study of Frequent Itemset Mining Techniques on Graphics Processor
, 2020 : Frequent itemset mining (FIM) is a core area for many data mining applications as association rules computation, clustering and correlations, which has been comprehensively studied over the last decades.
Prof Patel Chhaya, Dharmesh Bhalodiya
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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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