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 language | English |
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Pages (from-to) | 2659-2663 |
Number of pages | 5 |
Journal | IEICE Transactions on Information and Systems |
Volume | E100D |
Issue number | 10 |
DOIs | |
State | Published - 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