Results 251 to 260 of about 70,533 (290)

Task-Parallel FP-Growth on Cluster Computers

2010
Frequent itemset mining (FIM) is one of the most deeply studied data mining task. A number of algorithms, employing different approaches and advanced data structures, have already been proposed to solve the task efficiently. Even the fastest serial FIM algorithms fail to scale up with the rapid growth of database sizes.
Özdoğan, Gülistan Özdemir, Abul, O.
openaire   +2 more sources

MENENTUKAN POLA RESERVASI HOTEL DENGAN ALGORITMA FP-GROWTH

JATI (Jurnal Mahasiswa Teknik Informatika), 2023
Perkembangan industri perhotelan saat ini memang tumbuh dengan pesat, dan persaingan di antara para pengusaha hotel semakin ketat. Oleh karena itu, informasi yang tepat mengenai riwayat transaksi pemesanan hotel sangat penting bagi pihak manajemen hotel untuk dapat memahami perilaku konsumen serta membuat keputusan yang tepat dalam menjalankan bisnis ...
Jafar Jafar, Nining Rahaningsih
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FP-growth-algoritmi

2021
This bachelor's thesis studies FP-growth-algorithm, which is one of the association rule algorithm of data mining association method. Association rule algorithm finds the frequent itemsets and generates association rules based on those frequent itemsets.
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A Parallel FP-Growth Algorithm Based on GPU

2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), 2017
This paper proposes and implements a parallel scheme of FP-growth algorithm and implements this parallel algorithm (PFP-growth algorithm). Experimental results show that, compared with FP-growth algorithm, PFP-growth algorithm is more efficient, and the larger the data set is, the lower the support threshold is, the more remarkable the speedup is.
Hao Jiang, He Meng
openaire   +1 more source

Mining association rules uses fuzzy weighted FP-growth

The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 2012
In data mining, the association rules are used to search for the relations of items of the transactions database. Following the data collected and stored, it can find values through association rules, and assist manager to proceed marketing strategies and plan market framework.
Chien-Hua Wang, Sheng-Hsing Liu, Chin-Tzong Pang   +2 more
openaire   +1 more source

Quantum FP-Growth for Association Rules Mining

Quantum computing, based on quantum mechanics, promises revolutionary computational power by exploiting quantum states. It provides significant advantages over classical computing regarding time complexity, enabling faster and more efficient problem-solving.
Widad Hassina Belkadi, Yassine Drias, Habiba Drias   +2 more
openaire   +1 more source

DFPS: Distributed FP-growth algorithm based on Spark

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017
Frequent Itemset Mining (FIM) is the most important and time-consuming step of association rules mining. With the increment of data scale, many efficient single-machine algorithms of FIM, such as FP-growth and Apriori, cannot accomplish the computing tasks within reasonable time.
Xiujin Shi, Shaozong Chen, Hui Yang
openaire   +1 more source

Paths sharing based FP-growth data mining algorithms

2016 8th International Conference on Wireless Communications & Signal Processing (WCSP), 2016
Due to the network alarm data in cloud environment has the characteristics of massive, redundancy, relevance, etc., traditional FP-Growth algorithm has memory and computing time double bottleneck. Therefore, this paper presents an improved FP-Growth algorithm, which based on sharing path.
Shandong Ji, Dengyin Zhang, Liu Zhang
openaire   +1 more source

Integrating Spectral-CF and FP-Growth for Recommendation

Proceedings of the 2019 2nd International Conference on E-Business, Information Management and Computer Science, 2019
In the era of information overload, both information consumers and information producers have encountered great challenges: for information consumers, it is very difficult to find information of interest from a large amount of information. The recommendation system is an important tool to resolve this contradiction.
HuaXin Zhang, Yu Liu, KeYin Cao
openaire   +1 more source

FP-Growth Policy Mining for Access Control Policies

2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), 2018
In this paper we propose a technique known as FPgrowth algorithm to mining association rules. FP(Frequent Pattern) growth algorithm propose compressed information needed to frequent item set in FP-tree and FP-tree are finds all frequent item. The idea of Attribute Based Access Control has existed for decades.
Ajinkya Kalaskar, Vishali Barkade
openaire   +1 more source