Results 101 to 110 of about 659,904 (212)

Inverted Index Automata Frequent Itemset Mining for Large Dataset Frequent Itemset Mining

IEEE Access
Frequent itemset mining (FIM) faces significant challenges with the expansion of large-scale datasets. Traditional algorithms such as Apriori, FP-Growth, and Eclat suffer from poor scalability and low efficiency when applied to modern datasets ...
Xin Dai, Haza Nuzly Abdull Hamed, Qichen Su, Xue Hao   +3 more
doaj   +1 more source

Closed frequent itemset mining with arbitrary side constraints [PDF]

, 2018
Frequent itemset mining (FIM) is a method for finding regularities in transaction databases. It has several application areas, such as market basket analysis, genome analysis, and drug design. Finding frequent itemsets allows further analysis to focus on
Nightingale, Peter William, Ozgur Akgun, Kocak, Gokberk, Peter Nightingale, Gokberk Kocak, Akgun, Ozgur, Miguel, Ian James, Ian Miguel   +7 more
core   +1 more source

Penerapan Algoritma Apriori Untuk Membantu Calon Mahasiswa Dalam Memilih Program Studi Di Fakultas Ilmu Komputer Universitas Dian Nuswantoro

JOINS (Journal of Information System), 2017
Abstrak Menuut Educational Psychologist dari Integrity Development Flexibility (IDF) Irene Guntur, M.Psi., CGA, sebanyak 87%mahasiswa di Indonesia salahjurusan.Sering terjadi ketidakseimbangan antara jumlah mahasiswa yang diterima dengan jumlah ...
Marshela Dinda Amalia, Lalang Erawan
doaj  

Accelerating Parallel Frequent Itemset Mining on Graphics Processors with Sorting

, 2013
Part 4: Session 4: Multi-core Computing and GPUInternational audienceFrequent Itemset Mining (FIM) is one of the most investigated fields of data mining.
Hsu, Ching-Hsien, Ching-Hsien Hsu, Yu, Kun-Ming, Liu, Sheng-Hui, Huang, Yuan-Shao, Zhou, Li-Wei, Li-Wei Zhou, Yuan-Shao Huang, Kun-Ming Yu, Sheng-Hui Liu   +9 more
core   +1 more source

Itemset mining: A constraint programming perspective

Artificial Intelligence, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guns, Tias, Nijssen, Siegfried, De Raedt, Luc   +2 more
openaire   +2 more sources

CoverSize: A Global Constraint for Frequency-based Itemset Mining

, 2017
Constraint Programming is becoming competitive for solving certain data-mining problems largely due to the development of global constraints. We introduce the CoverSize constraint for itemset mining problems, a global constraint for counting and ...
Aoga, John, Guns, Tias, Principles and Practice of Constraint Programming - CP, Schaus, Pierre   +3 more
core   +2 more sources

Frequent itemset mining in high dimensional data: a review [PDF]

, 2018
This paper provides a brief overview of the techniques used in frequent itemset mining. It discusses the search strategies used; i.e. depth first vs. breadth-first, and dataset representation; i.e. horizontal vs. vertical representation.
Nurul Fariza Zulkurnain, Fatimah Audah Md. Zaki, Md. Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza   +3 more
core   +1 more source

Practical Approaches for Mining Frequent Patterns in Molecular Datasets

Bioinformatics and Biology Insights, 2016
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously accumulating biological data. Numerous itemset mining algorithms have been developed in the last decade to efficiently detect specific pattern classes in
Stefan Naulaerts, Sandy Moens, Kristof Engelen, Wim Vanden Berghe, Bart Goethals, Kris Laukens, Pieter Meysman   +6 more
doaj   +1 more source

Similarity processing in multi-observation data [PDF]

, 2012
Many real-world application domains such as sensor-monitoring systems for environmental research or medical diagnostic systems are dealing with data that is represented by multiple observations.
Bernecker, Thomas, Thomas Bernecker
core   +1 more source

Geometrically Inspired Itemset Mining

, 2008
In our geometric view, an itemset is a vector (itemvector) in the space of transactions. The support of an itemset is the generalized dot product of the participating items.
Florian Verhein, Sanjay Chawla
core