F Meziane
A system to support the identification and extraction of information related to privacy policies in electronic commerce websites
Meziane, F; Kasiran, MK; Prince, P
Authors
MK Kasiran
P Prince
Abstract
Privacy has been identified by many studies as the main problem why customers are not completing their online transactions. They fear to provide sensitive information such as personal and financial details. It is not surprising that most websites nowadays include privacy statements in their websites to encourage customers to complete their transactions. However, only few customers can find this information easily on merchants’ websites rendering the use of this information obsolete. The aim of this paper is two folds. First it identifies the link or document dealing with private policies on the website for the customer to consult. However, as the current research shows, these documents are long, tedious to read and contain information that may not be relevant to customers. The second aim of this paper is to automatically extract the most relevant information to the customer in the form of short statement. These statements include information on sharing and selling of personal details, the use of secure technologies, customer satisfaction with the goods purchased, the use of cookies and unsolicited communications. We use the Semantic distance similarity model as the basis to develop the information extraction component.
Citation
Meziane, F., Kasiran, M., & Prince, P. (2009, July). A system to support the identification and extraction of information related to privacy policies in electronic commerce websites. Presented at The Fourth European Conference on Intelligent Management systems in Operations, Salford, UK
Presentation Conference Type | Other |
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Conference Name | The Fourth European Conference on Intelligent Management systems in Operations |
Conference Location | Salford, UK |
Start Date | Jul 7, 2009 |
End Date | Jul 8, 2009 |
Publication Date | Jul 1, 2009 |
Deposit Date | Sep 11, 2009 |
Publicly Available Date | Sep 11, 2009 |
Additional Information | Event Type : Conference |
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