The week's pick
Reseach Article
Ranking Optimization using Outlier Detection Technique
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 123 - Number 3 |
| Year of Publication: 2015 |
| Authors: Yogendra Mahate, Roopam Gupta, Sanjeev Sharma |
10.5120/ijca2015905257
|
Yogendra Mahate, Roopam Gupta, Sanjeev Sharma . Ranking Optimization using Outlier Detection Technique. International Journal of Computer Applications. 123, 3 ( August 2015), 11-14. DOI=10.5120/ijca2015905257
Abstract
Product ranking optimization is an emerging required research area where we are getting a heavy duly competition day by day, number of products with sort of ranges are available in market, finding the best out of the different product is a major problem, several times it observed that number of survey has been made in order to make a product ranking and show it to users about the best available product for their requirement in the market, the ranking been held on multiple required attributes work or play the role to increase or decrease their ranking. Existing Line-up technique is only provided rank to number of products. It did not optimize the ranking. Now, in this paper, defeat these entire problems and provide the best solution. Introduce the outlier detection technique to optimize the product ranking according to requirement feature or attribute. Here i am going to implement some algorithm to detect best outliers such as distributing solving set algorithm, line-up algorithm & improved LAZY DSS.
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