@article{(Open Science Index):https://publications.waset.org/pdf/10007377,
	  title     = {Road Accidents Bigdata Mining and Visualization Using Support Vector Machines},
	  author    = {Usha Lokala and  Srinivas Nowduri and  Prabhakar K. Sharma},
	  country	= {},
	  institution	= {},
	  abstract     = {Useful information has been extracted from the
road accident data in United Kingdom (UK), using data analytics
method, for avoiding possible accidents in rural and urban areas.
This analysis make use of several methodologies such as data
integration, support vector machines (SVM), correlation machines
and multinomial goodness. The entire datasets have been imported
from the traffic department of UK with due permission. The
information extracted from these huge datasets forms a basis for
several predictions, which in turn avoid unnecessary memory
lapses. Since data is expected to grow continuously over a period
of time, this work primarily proposes a new framework model
which can be trained and adapt itself to new data and make
accurate predictions. This work also throws some light on use of
SVM’s methodology for text classifiers from the obtained traffic
data. Finally, it emphasizes the uniqueness and adaptability of
SVMs methodology appropriate for this kind of research work.},
	    journal   = {International Journal of Computer and Systems Engineering},
	  volume    = {10},
	  number    = {8},
	  year      = {2016},
	  pages     = {1517 - 1522},
	  ee        = {https://publications.waset.org/pdf/10007377},
	  url   	= {https://publications.waset.org/vol/116},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 116, 2016},
	}