Results 111 to 120 of about 2,811 (218)

Support Estimation in Frequent Itemset Mining by Locality Sensitive Hashing

, 2019
S.156-160The main computational effort in generating all frequent itemsets in a transactional database is in the step of deciding whether an itemset is frequent, or not. We present a method for estimating itemset supports with two-sided error.
Horvath, Tamas, Pick, Annika, Wrobel, Stefan   +2 more
core   +1 more source

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  

Perbandingan Kecepatan dalam Pencarian Frequent Itemset antara Algoritma FP-Growth dan Cut Both Ways [PDF]

, 2009
Penggalian kaidah asosiasi (mining association rules ) merupakan salah satu proses data mining untuk menemukan pola dan aturan (rule ) dari sekumpulan data yang besar.
FatmaRikaFebriyana
core  

Probabilistic frequent pattern growth for itemset mining in uncertain databases

, 2012
. Frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques ap-plied on standard (certain) transaction databases.
Florian Verhein, Matthias Renz, Hans-peter Kriegel, Andreas Züfle, Thomas Bernecker   +4 more
core   +1 more source

Frequent Closed High-Utility Itemset Mining Algorithm Based on Leiden Community Detection and Compact Genetic Algorithm

IEEE Access
Traditional pattern mining algorithms are based on tree and linked list structures. However, they often only consider a single factor of frequency or utility and have to deal with exponential search spaces as well as generate numerous candidates.
Xiumei Zhao, Xincheng Zhong, Bing Han
doaj   +1 more source

Evaluating the Privacy Implications of Frequent Itemset Disclosure. [PDF]

ICT Syst Secur Priv Prot (2017), 2017
Serra E, Vaidya J, Akella H, Sharma A.
europepmc   +1 more source

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  

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  

Filtering SMS Spam Berdasarkan Naive Bayes Classifier dan Apriori Algorithm Frequent Itemset [PDF]

, 2016
SMS masih menjadi salah satu pelayanan terpenting dalam media komunikasi. Namun karena SMS murah dan banyak digunakan, maka banyak muncul SMS spam. Untuk menanggulanginya, dalam tugas akhir ini penulis menggunakan Naive Bayes Classifier dan Apriori ...
FAHRIZAL MASYHUR
core  

Frequent itemset mining on multiprocessor systems.

, 2014
Frequent itemset mining is an important building block in many data mining applications like market basket analysis, recommendation, web-mining, fraud detection, and gene expression analysis. In many of them, the datasets being mined can easily grow up to hundreds of gigabytes or even terabytes of data.
openaire   +3 more sources