Results 31 to 40 of about 1,634,075 (173)

A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM

IEEE Access
Frequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf, M. Asif Naeem, Heejeong Jasmine Lee   +2 more
doaj   +1 more source

Weighted Association Rule Mining using Weighted Support and Significance Framework [PDF]

, 2003
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to handle weighted association rule mining problems where each item is allowed to
Murtagh, Fionn, Tao, Feng, Farid, Mohsen
core   +2 more sources

Perencanaan Pengembangan Aplikasi Penggalian Top-K Frequent Closed Constrained Gradient Itemsets Pada Basis Data Retail [PDF]

, 2008
Dalam dunia retail, pihak manajemen dapat memanfaatkan pengetahuan yang dapat dianalisis dari basis data retail untuk memahami pola kebutuhan pelanggan. Informasi ini dapat digunakan untuk membantu membuat keputusan bisnis.
Djunaidy, Arif, Absari, Dhiani Tresna
core   +2 more sources

Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle

BMC Bioinformatics, 2006
Background AMP-activated protein kinase (AMPK) has emerged as a significant signaling intermediary that regulates metabolisms in response to energy demand and supply.
Chen Yi-Ping, Chen Qingfeng
doaj   +1 more source

Finding Fuzzy Close Frequent Itemsets from Databases

Procedia Computer Science, 2018
Abstract In this paper, we define the problem of fuzzy close frequent itemset mining to discover the rules of the data. A concise tree-based data synoposis named FCTree is built, where the fuzzy itemsets are sorted by their supports. In addition, an algorithm called FCFIMiner is proposed to construct and maintain the FCTree . We conduct superset
Haifeng Li 0006, Yuejin Zhang, Mo Hai, Hanqing Hu   +3 more
openaire   +2 more sources

Maintaining frequent closed itemsets over a sliding window [PDF]

Journal of Intelligent Information Systems, 2007
In this paper, we study the incremental update of Frequent Closed Itemsets (FCIs) over a sliding window in a high-speed data stream. We propose the notion of semi-FCIs, which is to progressively increase the minimum support threshold for an itemset as it is retained longer in the window, thereby drastically reducing the number of itemsets that need to ...
James Cheng, Yiping Ke, Wilfred Ng
openaire   +3 more sources

Efficient Incremental Mining of Top-K Frequent Closed Itemsets

, 2007
In this work we study the mining of top-$K$ frequent closed itemsets, a recently proposed variant of the classical problem of mining frequent closed itemsets where the support threshold is chosen as the maximum value sufficient to guarantee that the ...
PIETRACAPRINA, ANDREA ALBERTO, VANDIN, FABIO   +1 more
core   +1 more source

AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION [PDF]

Journal of Engineering Science and Technology, 2017
Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes.
CHANDRASEKAR RAVI, NEELU KHARE
doaj  

Optimized Closed Frequent High Utility Itemset Mining Using OSR, OWL, and MSU Pruning on Retail Transaction Data

JUTI: Jurnal Ilmiah Teknologi Informasi
This research proposes the optimization of the Frequent Closed High-Utility Itemset Mining (FCHUIM) algorithm for retail transaction datasets using heuristic-based pruning techniques, Observed Support Ratio (OSR), Observed Weighted Lift (OWL), and ...
Kinana Syah Sulanjari, Chastine Fatichah
doaj   +1 more source

Mining frequent itemsets a perspective from operations research [PDF]

Many papers on frequent itemsets have been published. Besides somecontests in this field were held. In the majority of the papers the focus ison speed. Ad hoc algorithms and datastructures were introduced.
Kosters, W.A., Pijls, W.H.L.M.
core