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An Approach To Analyze Different Route Factors Using Hadoop Framework

D. Swetha Priya M. Humera Khanam1

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-12 , Page no. 794-798, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i12.794798

Online published on Dec 31, 2018

Copyright © D. Swetha Priya M. Humera Khanam . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: D. Swetha Priya M. Humera Khanam, “An Approach To Analyze Different Route Factors Using Hadoop Framework,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.794-798, 2018.

MLA Style Citation: D. Swetha Priya M. Humera Khanam "An Approach To Analyze Different Route Factors Using Hadoop Framework." International Journal of Computer Sciences and Engineering 6.12 (2018): 794-798.

APA Style Citation: D. Swetha Priya M. Humera Khanam, (2018). An Approach To Analyze Different Route Factors Using Hadoop Framework. International Journal of Computer Sciences and Engineering, 6(12), 794-798.

BibTex Style Citation:
@article{Khanam_2018,
author = {D. Swetha Priya M. Humera Khanam},
title = {An Approach To Analyze Different Route Factors Using Hadoop Framework},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2018},
volume = {6},
Issue = {12},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {794-798},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3417},
doi = {https://doi.org/10.26438/ijcse/v6i12.794798}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i12.794798}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3417
TI - An Approach To Analyze Different Route Factors Using Hadoop Framework
T2 - International Journal of Computer Sciences and Engineering
AU - D. Swetha Priya M. Humera Khanam
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 794-798
IS - 12
VL - 6
SN - 2347-2693
ER -

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Abstract

Whenever a person travelling from one place to another place. There are different routes between different regions. A person travelling from source to destination chooses a path based on different factors. Route choices from source to destination play an important role. It helps the user to choose the best route from many routes present based on different considerations. The traveller chooses the route with best factors like less time and distance. Such types of route factors are the main reasons to choose the route. We here develop a visual analytic system to display few more route choices. Here, based on the route factors the route with best factors is chosen as the best path and viewed to the user. We study and analyse route factors based on dataset. We analyse the dataset and a system with best and multiple route factors is developed using hadoop Framework.

Key-Words / Index Term

Route factors , Hadoop Framework, Big data

References

[1] Y. Zheng, L. Capra, O. Wolfson, and H. Yang, “Urban computing: concepts, methodologies, and applications,” ACM Transactions on Intelligent Systems and Technology (TIST), vol. 5, no. 3, p. 38, 2014.
[2] Vaishali Y. Chandurkar “A Survey on Evaluation of Traffic Mobility Using Clustering” International Journal of Innovative Research in Computer and Communication Engineering.
[3] Alessandro Vacca a, Italo Meloni “Understanding route switch behavior: an analysis using GPS based data” Transportation Research Procedia 5 ( 2015 ) 56 – 65
[4] W. Liu, Y. Zheng, S. Chawla, J. Yuan, and X. Xing, “Discovering spatiotemporal causal interactions in traffic data streams,” in Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011, pp. 1010–1018
[5] J. Yuan, Y. Zheng, X. Xie, and G. Sun, “T-Drive: enhancing driving directions with taxi drivers’ intelligence,” IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 1, pp. 220–232, 2013. Carlo Giacomo Prato, Victoria Gitelman and Shlomo, “Mapping patterns of pedestrian fatal accidents in Israel”, Accident Analysis and Prevention, pp.54–62, Jan 2012.
[6] H. Li, R. Guensler, and J. Ogle, “Analysis of morning commute route choice patterns using global positioning system-based vehicle activity data,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1926.1, pp. 162–170, 2005.
[7] Shlomo Bekhor, Moshe E. Ben-Akiva, M.Scott Ramming, “Evaluation of choice set generation algorithms,” Springer science, 2006.