Results 31 to 40 of about 1,488,747 (207)
DISCOVERING CONFUSING FREQUENT ITEMSETS
Tạp chí Khoa học Đại học Đà Lạt, 2018 Frequent itemset mining is one of the most important research areas in the field of association rule mining. Exploiting frequent itemsets at different abstraction levels of data will yield valuable knowledge.
Huỳnh Thành Lộc
doaj +1 more source
Hybrid Parallel Frequent Itemsets Mining Algorithm by Using N-List Structure [PDF]
Jisuanji kexue yu tansuo, 2022 Aiming at the problem of unbalanced load, bad efficiency of N-list merge and redundant search for each node based on parallel frequent itemset mining algorithm MRPrePost (parallel PrePost algorithm based on MapReduce), this paper proposes a hybrid ...
LIU Weiming, ZHANG Chi, MAO Yimin
doaj +1 more source
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi, 2016 AbstrakAlgoritma yang umum digunakan dalam proses pencarian frequent itemset (data yang paling sering muncul) adalah Apriori. Tetapi Algoritma Apriori mempunyai memiliki kekurangan yaitu membutuhkan waktu yang lama dalam proses pencarian frequent itemset.
Wirdah Choiriah
doaj +3 more sources
Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree
IEEE Access, 2020 Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on.
Jun-Feng Qu +5 more
doaj +1 more source
Frequent Itemset Mining using QUBO [PDF]
, 2022 In this paper we propose a R-step approximation to solve frequent itemset mining on quantum hardware like quantum annealing or QAOA. The idea is to search for the set of items where the minimal 2-item frequency is maximal.
Nüßlein, Jonas
core +1 more source
EFFICIENT FREQUENT ITEMSET DISCOVERY THROUGH HIERARCHICAL HUFFMAN ENCODING [PDF]
ICTACT Journal on Soft ComputingFrequent itemsets mining holds a crucial position in the field of data mining; however, traditional algorithms like Apriori and FP-Growth often encounter efficiency and memory consumption issues when handling large-scale datasets, which not only makes ...
Dai Xin, Hao Xue
doaj +1 more source
A Hybrid Approach for Mining Frequent Itemsets [PDF]
2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013 Frequent item set mining is a fundamental element with respect to many data mining problems. Recently, the PrePost algorithm has been proposed, a new algorithm for mining frequent item sets based on the idea of N-lists. PrePost in most cases outperforms other current state-of-the-art algorithms.
Bay Vo +3 more
openaire +2 more sources
Frequent itemset mining: technique to improve eclat based algorithm [PDF]
, 2019 In frequent itemset mining, the main challenge is to discover relationships between data in a transactional database or relational database. Various algorithms have been introduced to process frequent itemset.
Jalil, Masita Abdul +3 more
core +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
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