Results 31 to 40 of about 8,898 (200)
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets [PDF]
, 2009 As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications.
Kirsch, Adam +5 more
core +3 more sources
Majalah Ilmiah Teknologi Elektro, 2018 Algoritma FP-growth adalah algoritma data mining yang digunakan untuk menemukan frequent itemset pada data keranjang belanja. Frequent itemset adalah kelompok barang yang sering dibeli bersamaan dalam satu keranjang belanja. Analisa frequent itemset akan
I Gusti Agung Indrawan +2 more
doaj +1 more source
Video Mining with Frequent Itemset Configurations [PDF]
, 2006 We present a method for mining frequently occurring objects and scenes from videos. Object candidates are detected by finding recurring spatial arrangements of affine covariant regions. Our mining method is based on the class of frequent itemset mining algorithms, which have proven their efficiency in other domains, but have not been applied to video ...
Quack, Till +2 more
openaire +2 more sources
Frequent Itemset Mining and Association Rules [PDF]
, 2006 With the advent of mass storage devices, databases have become larger and larger. Point-of-sale data, patient medical data, scientific data, and credit card transactions are just a few sources of the ever-increasing amounts of data. These large datasets provide a rich source of useful information.
Imberman S., Tansel A.U.
openaire +3 more sources
An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data
Data, 2022 Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find
Mohamed Reda Al-Bana +2 more
doaj +1 more source
Peak-Jumping Frequent Itemset Mining Algorithms [PDF]
, 2006 We analyze algorithms that, under the right circumstances, permit efficient mining for frequent itemsets in data with tall peaks (large frequent itemsets). We develop a family of level-by-level peak-jumping algorithms, and study them using a simple probability model. The analysis clarifies why the jumping idea sometimes works well, and which properties
Dexters, Nele +2 more
openaire +2 more sources
Mining data quality rules based on T-dependence [PDF]
, 2019 Since their introduction in 1976, edit rules have been a standard tool in statistical analysis. Basically, edit rules are a compact representation of non-permitted combinations of values in a dataset.
Boeckling, Toon +2 more
core +1 more source
DiffNodesets: An Efficient Structure for Fast Mining Frequent Itemsets
, 2015 Mining frequent itemsets is an essential problem in data mining and plays an important role in many data mining applications. In recent years, some itemset representations based on node sets have been proposed, which have shown to be very efficient for ...
Deng, Zhi-Hong
core +1 more source
Proof Learning in PVS With Utility Pattern Mining
IEEE Access, 2020 Interactive theorem provers (ITPs) are software tools that allow human users to write and verify formal proofs. In recent years, an emerging research area in ITPs is proof mining, which consists of identifying interesting proof patterns that can be used ...
M. Saqib Nawaz +2 more
doaj +1 more source
Generic Itemset Mining Based on Reinforcement Learning
IEEE Access, 2022 One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj +1 more source