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Taxicab Geometry Based Analysis on Skyline for Business Intelligence

Taxicab Geometry Based Analysis on Skyline for Business Intelligence

Partha Ghosh, Takaaki Goto, Soumya Sen
Copyright: © 2018 |Volume: 6 |Issue: 4 |Pages: 17
ISSN: 2166-7160|EISSN: 2166-7179|EISBN13: 9781522546863|DOI: 10.4018/IJSI.2018100107
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MLA

Ghosh, Partha, et al. "Taxicab Geometry Based Analysis on Skyline for Business Intelligence." IJSI vol.6, no.4 2018: pp.86-102. http://doi.org/10.4018/IJSI.2018100107

APA

Ghosh, P., Goto, T., & Sen, S. (2018). Taxicab Geometry Based Analysis on Skyline for Business Intelligence. International Journal of Software Innovation (IJSI), 6(4), 86-102. http://doi.org/10.4018/IJSI.2018100107

Chicago

Ghosh, Partha, Takaaki Goto, and Soumya Sen. "Taxicab Geometry Based Analysis on Skyline for Business Intelligence," International Journal of Software Innovation (IJSI) 6, no.4: 86-102. http://doi.org/10.4018/IJSI.2018100107

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Abstract

This article describes how multi-criteria decision making problems are difficult to handle in normal SQL query processing. Skyline computation is generally used to solve these types of requirements by using dominance analysis and finding shortest distance with respect to a prime interesting point. However, in real life scenarios shortest distance may not be applicable in most of the cases due to different obstacles or barriers exist between the point of interests or places. In order to consider the presence of obstacles for geographically dispersed data, this research work uses Taxicab geometry for distance calculation, which is a simple Non-Euclidian geometry with minimum time complexity. Another limitation of previous skyline based works are that they only focus upon a single interesting point and can't be apply for multiple interesting points. This research article focuses upon multiple visiting points for the travelers in an optimized way. In addition to this, the article also selects areas for setting up of new business properties considering the constraints.

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