Publication Type:

Conference Paper

Source:

2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, Institute of Electrical and Electronics Engineers Inc. (2017)

ISBN:

9781509006113

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020007665&doi=10.1109%2fICCIC.2016.7919699&partnerID=40&md5=56fa010512f0e2ff7d04ac6e14353d0b

Keywords:

Admission Analysis, Artificial intelligence, Average Distance, Clustering algorithms, Commerce, Data mining, Distance calculation, Educational organizations, Haversine Formulae, Heterogeneous data sources, Housing, k-Means algorithm, Marketing, Pictorial representation, Students

Abstract:

Data mining is defined as extracting and analyzing information from various heterogeneous data sources to generate the user interested patterns. In this paper, data mining is used for such a purpose where in which it helps in increasing the marketing of a respective educational organization. Students will come from different localities to join a prospective college. In the proposed system, instead of places, the distance from the address of the student residence destination is analyzed. It provides a more accurate idea about the upcoming year marketing. Distance can be calculated by using the Haversines formula and the clustering algorithm k-means can be used to cluster the locations to get more accurate results. Google maps API is used to find out the latitude and longitude of each student residential address and visualized, which gives the minimum, maximum and average distance. The pictorial representation helps the organizations to concentrate more on specific areas where the better advertisement can be given to improving the admission rate. © 2016 IEEE.

Notes:

cited By 0; Conference of 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016 ; Conference Date: 15 December 2016 Through 17 December 2016; Conference Code:127661

Cite this Research Publication

V. Hegde, Aswathi, T. S., and Sidharth, R., “Student residential distance calculation using Haversine formulation and visualization through GoogleMap for admission analysis”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, 2017.

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