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On verifying the authenticity of e-commercial crawling data by a semi-crosschecking method

Tran Khanh Dang (Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam)
Duc Minh Chau Pham (Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam)
Duc Dan Ho (Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam)

International Journal of Web Information Systems

ISSN: 1744-0084

Article publication date: 3 June 2019

Issue publication date: 20 September 2019

298

Abstract

Purpose

Data crawling in e-commerce for market research often come with the risk of poor authenticity due to modification attacks. The purpose of this paper is to propose a novel data authentication model for such systems.

Design/methodology/approach

The data modification problem requires careful examinations in which the data are re-collected to verify their reliability by overlapping the two datasets. This approach is to use different anomaly detection techniques to determine which data are potential for frauds and to be re-collected. The paper also proposes a data selection model using their weights of importance in addition to anomaly detection. The target is to significantly reduce the amount of data in need of verification, but still guarantee that they achieve their high authenticity. Empirical experiments are conducted with real-world datasets to evaluate the efficiency of the proposed scheme.

Findings

The authors examine several techniques for detecting anomalies in the data of users and products, which give the accuracy of 80 per cent approximately. The integration with the weight selection model is also proved to be able to detect more than 80 per cent of the existing fraudulent ones while being careful not to accidentally include ones which are not, especially when the proportion of frauds is high.

Originality/value

With the rapid development of e-commerce fields, fraud detection on their data, as well as in Web crawling systems is new and necessary for research. This paper contributes a novel approach in crawling systems data authentication problem which has not been studied much.

Keywords

Citation

Dang, T.K., Pham, D.M.C. and Ho, D.D. (2019), "On verifying the authenticity of e-commercial crawling data by a semi-crosschecking method", International Journal of Web Information Systems, Vol. 15 No. 4, pp. 454-473. https://doi.org/10.1108/IJWIS-10-2018-0075

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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