Results 91 to 100 of about 2,811 (218)

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
Feng Tao, Murtagh, Fionn, Mohsen Farid, Tao, Feng, Fionn Murtagh, Farid, Mohsen   +5 more
core   +1 more source

Efficiently Mining Frequent Itemsets on Massive Data

IEEE Access, 2019
Frequent itemset mining is an important operation to return all itemsets in the transaction table, which occur as a subset of at least a specified fraction of the transactions.
Xixian Han, Xianmin Liu, Jian Chen, Guojun Lai, Hong Gao, Jianzhong Li   +5 more
doaj   +1 more source

Memory issues in frequent itemset mining

, 2004
During the past decade, many algorithms have been proposed to solve the frequent itemset mining problem, i.e. find all sets of items that frequently occur together in a given database of transactions.
Goethals, Bart, Bart Goethals
core   +1 more source

Frequent Itemset Mining in Big Data With Effective Single Scan Algorithms

IEEE Access, 2018
This paper considers frequent itemsets mining in transactional databases. It introduces a new accurate single scan approach for frequent itemset mining (SSFIM), a heuristic as an alternative approach (EA-SSFIM), as well as a parallel implementation on ...
Youcef Djenouri, Djamel Djenouri, Jerry Chun-Wei Lin, Asma Belhadi   +3 more
doaj   +1 more source

IMPLEMENTASI ALGORITMA APRIORI UNTUK MENEMUKAN FREQUENT ITEMSET DALAM KERANJANG BELANJA

, 2016
Algoritma apriori menggunakan pendekatan iteratif dimana k-itemset digunakan untuk mengeksplorasi (k+1)-itemset. Calon (k+1)-itemset yang mengandung frekuensi subset yang jarang muncul atau dibawah threshold akan dipangkas dan tidak dipakai menentukan ...
I Ketut Gede Darma Putra, Adie Wahyudi Oktavia Gama, I Putu Agung Bayupati   +2 more
core  

Mining frequent sequences using itemset-based extension [PDF]

, 2008
In this paper, we systematically explore an itemset-based extension approach for generating candidate sequence which contributes to a better and more straightforward search space traversal performance than traditional item-based extension approach. Based
Xu, Yusheng, Dillon, Tharam S., Ma, Zhixin, Chen, Xiaoyun   +3 more
core  

Probabilistic Support Prediction: Fast Frequent Itemset Mining in Dense Data

IEEE Access
Frequent itemset mining (FIM) is a highly resource-demanding data-mining task fundamental to numerous data-mining applications. Support calculation is a frequently performed computation-intensive operation of FIM algorithms, whereas storing transactional
Muhammad Sadeequllah, Azhar Rauf, Saif Ur Rehman, Noha Alnazzawi   +3 more
doaj   +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, Zheng Pei, Keyun Qin, Mingming Kong   +3 more
doaj   +1 more source

Comparison of Candidate Itemset Generation and Non Candidate Itemset Generation Algorithms in Mining Frequent Patterns

, 2017
Association rule mining is one of the important techniques of data mining used for exploring fruitful patterns from huge collection of data. Generally, the finding of frequent itemsets is the most significant step in association rules mining, and most of
, M.Sinthuja, N. Puviarasan, P. Aruna
core   +1 more source

Mining frequent itemsets a perspective from operations research

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