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Rare item detection in e-commerce site

Published: 20 April 2009 Publication History

Abstract

As the largest online marketplace in the world, eBay has a huge inventory where there are plenty of great rare items with potentially large, even rapturous buyers. These items are obscured in long tail of eBay item listing and hard to find through existing searching or browsing methods. It is observed that there are great rarity demands from users according to eBay query log. To keep up with the demands, the paper proposes a method to automatically detect rare items in eBay online listing. A large set of features relevant to the task are investigated to filter items and further measure item rareness. The experiments on the most rarity-demand-intensitive domains show that the method may effectively detect rare items (>90% precision).

Reference

[1]
C. Anderson. The long tail. Wired, Oct. 2004.

Cited By

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  • (2017)Enhancing long tail item recommendations using tripartite graphs and Markov processProceedings of the International Conference on Web Intelligence10.1145/3106426.3106439(761-768)Online publication date: 23-Aug-2017
  • (2017)Using tripartite graphs to make long tail recommendations2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA.2017.8316436(1-6)Online publication date: Aug-2017

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cover image ACM Conferences
WWW '09: Proceedings of the 18th international conference on World wide web
April 2009
1280 pages
ISBN:9781605584874
DOI:10.1145/1526709

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2009

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Author Tags

  1. long tail theory
  2. rare item detection
  3. rareness measure

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all
  • (2017)Enhancing long tail item recommendations using tripartite graphs and Markov processProceedings of the International Conference on Web Intelligence10.1145/3106426.3106439(761-768)Online publication date: 23-Aug-2017
  • (2017)Using tripartite graphs to make long tail recommendations2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA.2017.8316436(1-6)Online publication date: Aug-2017

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