Improved Parallel Apriori Algorithm for Multi-cores | Zendy

Swati Rustogi | Zendy; Маниша Шарма | Zendy; Sudha Morwal | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Improved Parallel Apriori Algorithm for Multi-cores

Author(s) -

Swati Rustogi,

Маниша Шарма,

Sudha Morwal

Publication year - 2017

Publication title -

international journal of information technology and computer science

Language(s) - English

Resource type - Journals

eISSN - 2074-9015

pISSN - 2074-9007

DOI - 10.5815/ijitcs.2017.04.03

Subject(s) - computer science , apriori algorithm , speedup , a priori and a posteriori , parallelism (grammar) , set (abstract data type) , core (optical fiber) , algorithm , multi core processor , data mining , parallel computing , association rule learning , philosophy , epistemology , telecommunications , programming language

Apriori algorithm is one of the most popular data mining techniques, which is used for mining hidden relationship in large data. With parallelism, a large data set can be mined in less amount of time. Apart from the costly distributed systems, a computer supporting multi core environment can be used for applying parallelism. In this paper an improved Apriori algorithm for multi-core environment is proposed. The main contributions of this paper are: An efficient Apriori algorithm that applies data parallelism in multi-core environment by reducing the time taken to count the frequency of candidate item sets. The performance of proposed algorithm is evaluated for multiple cores on basis of speedup. The performance of the proposed algorithm is compared with the other such parallel algorithm and it shows an improvement by more than 15% preliminary experiment.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research