Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/101077
Title: Detecting imprudence of 'reliable' sellers in online auction sites
Authors: Liu, Xin
Datta, Anwitaman
Fang, Hui
Zhang, Jie
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Liu, X., Datta, A., Fang, H., & Zhang, J. (2012). Detecting imprudence of 'reliable' sellers in online auction sites. 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp.246-253.
Abstract: Reputation systems deployed in popular online auction sites simply aggregate feedback about a seller's past transactions. By studying a real auction site dataset, we infer that a non-negligible fraction of unsatisfactory transactions involve sellers with high reputation. Such a phenomenon can be interpreted by motivation theory from behaviorial science: A seller with high reputation has more business opportunities. Bad feedback for latest transactions do not immediately affect his reputation adequately to hurt business, hence he may not be as prudent as before. In this work, we propose the concept of imprudence to study and detect the inappropriate behavior of a 'reliable' seller (i.e., the one with high reputation computed using conventional approaches). Specifically, we first identify and verify the features that influence a seller's imprudence behavior. We then design a novel intelligent buying agent to combine these factors using logistic regression for predicting and studying the probability of imprudence of a target seller. We validate our approach using real datasets driven experiments.
URI: https://hdl.handle.net/10356/101077
http://hdl.handle.net/10220/16771
DOI: 10.1109/TrustCom.2012.123
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

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