Results 31 to 40 of about 8,356 (188)
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
ETP-Mine: An Efficient Method for Mining Transitional Patterns [PDF]
, 2010 A Transaction database contains a set of transactions along with items and their associated timestamps. Transitional patterns are the patterns which specify the dynamic behavior of frequent patterns in a transaction database.
Bhaskar, A., Kumar, B. Kiran
core +2 more sources
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
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 +5 more
doaj +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
Re-mining item associations: methodology and a case study in apparel retailing [PDF]
, 2010 Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items.
Atan, Tankut +4 more
core +1 more source
A weighted frequent itemset mining algorithm for intelligent decision in smart systems
IEEE Access, 2018 Intelligent decision is the key technology of smart systems. Data mining technology has been playing an increasingly important role in decision-making activities.
Xuejian Zhao +4 more
doaj +1 more source
Mining Top-K Frequent Itemsets Through Progressive Sampling
, 2010 We study the use of sampling for efficiently mining the top-K frequent itemsets of cardinality at most w. To this purpose, we define an approximation to the top-K frequent itemsets to be a family of itemsets which includes (resp., excludes) all very ...
Andrea Pietracaprina +8 more
core +1 more source
Frequent Itemsets Mining With Differential Privacy Over Large-Scale Data
IEEE Access, 2018 Frequent itemsets mining with differential privacy refers to the problem of mining all frequent itemsets whose supports are above a given threshold in a given transactional dataset, with the constraint that the mined results should not break the privacy ...
Xinyu Xiong +6 more
doaj +1 more source
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