Application of Modified OPTICS Algorithm in E-Commerce Sites Classification and Evaluation

Application of Modified OPTICS Algorithm in E-Commerce Sites Classification and Evaluation

Zhuoxi Yu (School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun, China), YuJia Jin (School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun, China), Milan Parmar (Hunan University of Arts and Science, Changde, China) and Limin Wang (School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun, China)
Copyright: © 2016 |Pages: 12
DOI: 10.4018/JECO.2016010106
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Abstract

In the era of the development in network economy, e-commerce sites' operational efficiency is in relation to the development of enterprises. Thus, how to evaluate e-commerce sites have become a hot topic. Due to the evaluation index of e-commerce sites have the characteristics of high dimension and data inhomogeneity, the new method combines PCA with the improved OPTICS algorithm to classify and evaluate the e-commerce demonstration enterprise websites. Firstly, using PCA to reduce the dimension of high-dimensional data. Secondly, for the limitation of OPTICS algorithm in dealing with sparse points, then using the improved OPTICS algorithm in clustering low-dimensional data to evaluate the effect of e-commerce sites and make suggestions.
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Intoduction Of Optics Algorithm And Principal Component Analysis

First, there is a simple introduction about the OPTICS algorithm. Due to the sites data having a characteristic of uneven density, OPTICS algorithm has the limitation in processing sparse points; second, for the shortcomings of the OPTICS algorithm, introducing the improved OPTICS algorithm.

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