Fraud detection in comparison-shopping services: Patterns and anomalies in user click behaviors

Sang Chul Lee, Christos Faloutsos, Dong Kyu Chae, Sang Wook Kim

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This paper deals with a novel, interesting problem of detecting frauds in comparison-shopping services (CSS). In CSS, there exist frauds who perform excessive clicks on a target item. They aim at making the item look very popular and subsequently ranked high in the search and recommendation results. As a result, frauds may distort the quality of recommendations and searches. We propose an approach of detecting such frauds by analyzing click behaviors of users in CSS. We evaluate the effectiveness of the proposed approach on a real-world clickstream dataset.

Original languageEnglish
Pages (from-to)2659-2663
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE100D
Issue number10
DOIs
StatePublished - Oct 2017

Bibliographical note

Publisher Copyright:
Copyright © 2017 The Institute of Electronics, Information and Communication Engineers.

Keywords

  • Comparison-shopping services
  • Fraud detection
  • User behavior analysis

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