NDLI: Using Stereotypes to Identify Risky Transactions in Internet Auctions

Content Provider	IEEE Xplore Digital Library
Author	Xin Liu Kaszuba, T. Nielek, R. Datta, A. Wierzbicki, A.
Copyright Year	2010
Abstract	Encountering unknown sellers is very common in online auction sites. In such a scenario, a buyer can not estimate trustworthiness of the unknown seller based on the seller's past behavior. The buyer is thus exposed to the risks of being cheated. In this paper we describe a stereotypes based mechanism to determine the risk of a potential transaction even if the seller is personally unknown to not only the buyer but also to the rest of the system. Specifically, our approach first identifies discriminating attributes which are capable of distinguishing successful transactions from unsuccessful ones. A buyer can use its own past transactions (with other sellers) to form such stereotypes. Alternatively, the community's collective knowledge can also be used to build such stereotypes. When posed to a potential transaction with an unknown seller, buyers can estimate trustworthiness (and thus the risk) by combining the corresponding stereotypes. We report experiments over real auction data collected from Allegro, a leading auction site in Eastern Europe. Data driven simulation results show that by setting suitable thresholds our approach can effectively detect (predict) frauds, i.e., has low false positive, with flagging very few successful transactions, that is, it has very low false negative. We also observe from these experiments that local knowledge derived stereotypes are the most accurate, since it is personalized for individual buyers. However, community knowledge derived stereotypes are particularly useful for inexperienced buyers that dominate online auction sites, though there is slight decrease in accuracy. We leverage such analytics to provide a browser (Firefox) based tool to guide buyers during live auctions.
Starting Page	513
Ending Page	520
File Size	377283
Page Count	8
File Format	PDF
ISBN	9781424484393
DOI	10.1109/SocialCom.2010.81
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Instruction sets Communities Crawlers Mobile handsets Internet Browsers Electronic mail Online auction Stereotypes Fraud detection Trust
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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