Sasmita Panigrahi

Work place: Department of Computer Science & Engineering, IIIT Bhubaneswar, India



Research Interests: Computer systems and computational processes, Artificial Intelligence, Computational Learning Theory, Data Mining, Data Structures and Algorithms


Sasmita Panigrahi has completed his M.Tech in Computer Science & Engineering from IIIT Bhubaneswar. Her research areas of interest include Machine Learning, Big data. Computational Intelligence and Data Mining.

Author Articles
An Improved Hybrid Distributed Collaborative Filtering Model for Recommender Engine using Apache Spark

By Rakesh K. Lenka Rabindra K. Barik Sasmita Panigrahi Sai S. Panda

DOI:, 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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