Work place: School of Computer Application, KIIT University, India
E-mail: rabindra.mnnit@gmail.com
Website:
Research Interests: Medical Informatics, Autonomic Computing, Data Structures and Algorithms, Mathematics of Computing
Biography
Dr. Rabindra K Barik is currently working as an Assistant Professor in the School of Computer Applications, KIIT University, Bhubaneswar, India. He has received his both M.Tech and Ph.D. in Geoinformatics from Motilal Nehru National Institute of Technology, Allahabad, India. His research area includes Geospatial Database, SOA, Cloud Computing, IPR and Geoinformatics. He is a member of IEEE and IAENG.
By Rakesh K. Lenka Rabindra K. Barik Sasmita Panigrahi Sai S. Panda
DOI: https://doi.org/10.5815/ijisa.2018.07.08, Pub. Date: 8 Jul. 2018
The present scenario there is a serious need of scalability for efficient analytics of big data. In order to achieve this, technology like MapReduce, Pig and HIVE came into action but when the question comes to scalability; Apache Spark maintains a great position far ahead. In this research paper, it has designed and developed an improved hybrid distributed collaborative model for filtering recommender engine. Execution time, scalability and robustness of the engine are the three evaluation parameters; has been considered for this present study. The present work keeps an eye on recommender system built with help of Apache Spark. Apart from this, it has been proposed and implemented the bisecting KMeans clustering algorithms. It has discussed about the comparative analysis between KMeans and Bisecting KMeans clustering algorithms on Apache Spark environment.
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