English

FAIR: A Hadoop-based Hybrid Model for Faculty Information Retrieval System

Distributed, Parallel, and Cluster Computing 2017-06-27 v1

Abstract

In era of ever-expanding data and knowledge, we lack a centralized system that maps all the faculties to their research works. This problem has not been addressed in the past and it becomes challenging for students to connect with the right faculty of their domain. Since we have so many colleges and faculties this lies in the category of big data problem. In this paper, we present a model which works on the distributed computing environment to tackle big data. The proposed model uses apache spark as an execution engine and hive as database. The results are visualized with the help of Tableau that is connected to Apache Hive to achieve distributed computing.

Keywords

Cite

@article{arxiv.1706.08018,
  title  = {FAIR: A Hadoop-based Hybrid Model for Faculty Information Retrieval System},
  author = {Noopur Gupta and Rakesh K. Lenka and Rabindra K. Barik and Harishchandra Dubey},
  journal= {arXiv preprint arXiv:1706.08018},
  year   = {2017}
}

Comments

6 pages, 11 figures, 2017 International Conference on Intelligent Computing and Control(I2C2'17), IEEE, June 23-24, 2017, Coimbatore, India

R2 v1 2026-06-22T20:28:41.262Z