Multi-dimensional e-commerce trust evaluation method

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the last decade, e-commerce has been grown rapidly and become a familiar tool of shopping for many people. However, some people still have concerns while making online purchases due to its uncertain attributes. In fact, there are many online consumers have suffered from monetary loose problem due to some reasons which the lack of the trust in e-commerce is one of them. Therefore, there is a great demand for a mechanism that helps to evaluate the trust throughout the online transactions. One of them is the existing mechanism of the trust management which is used in some e-commerce websites (e.g. eBay). Such a mechanism evaluates the trust by computing a trust value of any seller only based on the previous rating of the past transactions. Therefore, the trust value is only able to show the general status of the trust without taking into the account the new transaction. Consequently, there is a great possibility for the frauds to be committed by some of the malicious people. For example, some of them can easily build a good reputation by making many transactions by selling cheap products with good qualities and start to commit frauds by selling more expensive products. This kind of frauds is named by [1] as the value imbalance problem. Therefore, there is a great demand for a trust evaluation mechanism which consider the new transaction as well as the past transactions. In this paper, we propose a new method which considers three dimensions that play important roles in any online transaction to help the buyers to detect the frauds. This method measures the similarity between the new transaction and the past transactions in the products types dimension, the number of the products sold dimension and the transactions amounts dimension.
LanguageEnglish
Title of host publication2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA)
PublisherIEEE
Number of pages7
ISBN (Electronic)9781538691410
ISBN (Print)9781538691427
DOIs
StateE-pub ahead of print - 4 Feb 2019
Event12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA2018) - Phnom Penh, Cambodia
Duration: 3 Dec 20185 Dec 2018
https://ieeexplore.ieee.org/document/8631523

Publication series

NameIEEE Conference Proceedings
PublisherIEEE
ISSN (Print)2373-082X
ISSN (Electronic)2573-3214

Conference

Conference12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA2018)
Abbreviated titleSKIMA 2018
CountryCambodia
CityPhnom Penh
Period3/12/185/12/18
Internet address

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Keywords

  • context modeling
  • computational modeling
  • ontologies
  • automobiles
  • trust management
  • instruments
  • printers

Cite this

Alsharif, N., Dahal, K., Pervez, Z., & Sureephong, P. (2019). Multi-dimensional e-commerce trust evaluation method. In 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA) (IEEE Conference Proceedings). IEEE. DOI: 10.1109/SKIMA.2018.8631523
Alsharif, Nasser ; Dahal, Keshav ; Pervez, Zeeshan ; Sureephong, Pradorn . / Multi-dimensional e-commerce trust evaluation method. 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA). IEEE, 2019. (IEEE Conference Proceedings).
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abstract = "In the last decade, e-commerce has been grown rapidly and become a familiar tool of shopping for many people. However, some people still have concerns while making online purchases due to its uncertain attributes. In fact, there are many online consumers have suffered from monetary loose problem due to some reasons which the lack of the trust in e-commerce is one of them. Therefore, there is a great demand for a mechanism that helps to evaluate the trust throughout the online transactions. One of them is the existing mechanism of the trust management which is used in some e-commerce websites (e.g. eBay). Such a mechanism evaluates the trust by computing a trust value of any seller only based on the previous rating of the past transactions. Therefore, the trust value is only able to show the general status of the trust without taking into the account the new transaction. Consequently, there is a great possibility for the frauds to be committed by some of the malicious people. For example, some of them can easily build a good reputation by making many transactions by selling cheap products with good qualities and start to commit frauds by selling more expensive products. This kind of frauds is named by [1] as the value imbalance problem. Therefore, there is a great demand for a trust evaluation mechanism which consider the new transaction as well as the past transactions. In this paper, we propose a new method which considers three dimensions that play important roles in any online transaction to help the buyers to detect the frauds. This method measures the similarity between the new transaction and the past transactions in the products types dimension, the number of the products sold dimension and the transactions amounts dimension.",
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author = "Nasser Alsharif and Keshav Dahal and Zeeshan Pervez and Pradorn Sureephong",
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Alsharif, N, Dahal, K, Pervez, Z & Sureephong, P 2019, Multi-dimensional e-commerce trust evaluation method. in 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA). IEEE Conference Proceedings, IEEE, 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA2018), Phnom Penh, Cambodia, 3/12/18. DOI: 10.1109/SKIMA.2018.8631523

Multi-dimensional e-commerce trust evaluation method. / Alsharif, Nasser; Dahal, Keshav; Pervez, Zeeshan; Sureephong, Pradorn .

2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA). IEEE, 2019. (IEEE Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Dahal,Keshav

AU - Pervez,Zeeshan

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N2 - In the last decade, e-commerce has been grown rapidly and become a familiar tool of shopping for many people. However, some people still have concerns while making online purchases due to its uncertain attributes. In fact, there are many online consumers have suffered from monetary loose problem due to some reasons which the lack of the trust in e-commerce is one of them. Therefore, there is a great demand for a mechanism that helps to evaluate the trust throughout the online transactions. One of them is the existing mechanism of the trust management which is used in some e-commerce websites (e.g. eBay). Such a mechanism evaluates the trust by computing a trust value of any seller only based on the previous rating of the past transactions. Therefore, the trust value is only able to show the general status of the trust without taking into the account the new transaction. Consequently, there is a great possibility for the frauds to be committed by some of the malicious people. For example, some of them can easily build a good reputation by making many transactions by selling cheap products with good qualities and start to commit frauds by selling more expensive products. This kind of frauds is named by [1] as the value imbalance problem. Therefore, there is a great demand for a trust evaluation mechanism which consider the new transaction as well as the past transactions. In this paper, we propose a new method which considers three dimensions that play important roles in any online transaction to help the buyers to detect the frauds. This method measures the similarity between the new transaction and the past transactions in the products types dimension, the number of the products sold dimension and the transactions amounts dimension.

AB - In the last decade, e-commerce has been grown rapidly and become a familiar tool of shopping for many people. However, some people still have concerns while making online purchases due to its uncertain attributes. In fact, there are many online consumers have suffered from monetary loose problem due to some reasons which the lack of the trust in e-commerce is one of them. Therefore, there is a great demand for a mechanism that helps to evaluate the trust throughout the online transactions. One of them is the existing mechanism of the trust management which is used in some e-commerce websites (e.g. eBay). Such a mechanism evaluates the trust by computing a trust value of any seller only based on the previous rating of the past transactions. Therefore, the trust value is only able to show the general status of the trust without taking into the account the new transaction. Consequently, there is a great possibility for the frauds to be committed by some of the malicious people. For example, some of them can easily build a good reputation by making many transactions by selling cheap products with good qualities and start to commit frauds by selling more expensive products. This kind of frauds is named by [1] as the value imbalance problem. Therefore, there is a great demand for a trust evaluation mechanism which consider the new transaction as well as the past transactions. In this paper, we propose a new method which considers three dimensions that play important roles in any online transaction to help the buyers to detect the frauds. This method measures the similarity between the new transaction and the past transactions in the products types dimension, the number of the products sold dimension and the transactions amounts dimension.

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KW - computational modeling

KW - ontologies

KW - automobiles

KW - trust management

KW - instruments

KW - printers

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M3 - Conference contribution

SN - 9781538691427

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BT - 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA)

PB - IEEE

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Alsharif N, Dahal K, Pervez Z, Sureephong P. Multi-dimensional e-commerce trust evaluation method. In 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA). IEEE. 2019. (IEEE Conference Proceedings). Available from, DOI: 10.1109/SKIMA.2018.8631523