Results 101 to 110 of about 1,488,747 (207)

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
Zhixin Ma (11225671), Xiaoyun Chen (222968), Yusheng Xu (10588994), Tharam S. Dillon (23304517)   +3 more
core   +1 more source

Mining Approximate Frequent Itemset from Noisy Data

, 2005
Frequent itemset mining is a popular and important first step in analyzing data sets across a broad range of applications. The traditional, “exact ” approach for finding frequent itemsets requires that every item in the itemset occurs in each supporting ...
Susan Paulsen, Andrew Nobel, Wei Wang, Jan Prins, Jinze Liu   +4 more
core  

APLIKASI DATA MINING MARKET BASKET ANALYSIS PADA TABEL DATA ABSENSI ELEKTRONIK UNTUK MENDETEKSI KECURANGAN ABSENSI (CHECK-LOCK) KARYAWAN DI PERUSAHAAN

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, Felicia Soedjianto   +1 more
doaj  

kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets

, 2003
This paper presents the implementation of DCI++, an enhancement of DCI, a scalable algorithm for discovering frequent sets in large databases. The main contribution of DCI++ resides on a novel counting inference strategy, inspired by previously known ...
Lucchese C, Palmerini P, Perego R, Silvestri F, Orlando S   +4 more
core  

VizARE: An Intermediate Representation to Support the Visualization of Association Rules in Data Mining

Future Internet
Data mining techniques are currently highly useful and widely used in industry, business and government. However, their broad adoption is sometimes limited because non-expert users are required to accurately interpret and deal with the complex results ...
Carlos Fernandez-Basso, Maria Dolores Ruiz, Miguel Molina-Solana, Maria J. Martin-Bautista   +3 more
doaj   +1 more source

A Fuzzy Algorithm for Mining High Utility Rare Itemsets -FHURI

, 2014
Classical frequent itemset mining identifies frequent itemsets in transaction databases using only frequency of item occurrences, without considering utility of items.
Pillai, Jyothi, Uk, Vyas, O P, Muyeba, M Ac, Muyeba, Maybin K   +4 more
core  

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.

core  

Improved Algorithm for Frequent Itemsets Mining Based on Apriori and FP-Tree [PDF]

, 2013
Frequent itemset mining plays an important role in association rule mining.
Priti Chandra, B.L.Deekshatulu, Dr. Sujatha Dandu   +2 more
core  

A study of selected itemset mining and association rule mining algorithms

, 2022
Data Mining is a central step in Knowledge Discovery in Databases (KDD). This thesis is within the context of Data Mining and more specifically revolves around a couple the Data Mining tasks: Itemset Mining and Association Rule Mining.
Hammami, Rim
core  

Application of K-means supported by clustered systems in big data association rule mining

Systems and Soft Computing
s: 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
doaj   +1 more source