Work place: Department of Computer Science & Engineering, IIIT Bhubaneswar, India
Research Interests: Artificial Intelligence, Computational Learning Theory, Data Mining, Data Structures and Algorithms
Rakesh K. Lenka Rakesh K. Lenka has completed his M.Tech in Computer Science & Engineering from Motilal Nehru National Institute of Technology, Allahabad. Currently he is working as an Assistant Professor in the department of Computer Science and Engineering of IIIT Bhubaneswar and pursuing Ph.D. in VSSUT, Burla. His research areas of interest include Machine Learning, Computational Intelligence, Data Mining and Cloud Computing. He is a member of IEEE and CSI.
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.[...] Read more.
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