Work place: Banasthali Vidyapith, Rajasthan, India
E-mail: swati.rustogi@gmail.com
Website:
Research Interests: Artificial Intelligence, Image Compression, Image Manipulation, Image Processing
Biography
Swati Rustogi is currently pursuing Ph.D. (CS) from Banasthali Vidyapith, Rajasthan, India. She is working as an Assistant Professor with Amity University, Noida. She completed her graduation from Delhi University and MCA from Birla Institute of Applied Sciences.
She has seven years of teaching and research experience and five years of industry experience. In research she has been focusing on distributed systems.
By Swati Rustogi Manisha Sharma Sudha Morwal
DOI: https://doi.org/10.5815/ijitcs.2017.04.03, Pub. Date: 8 Apr. 2017
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.
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