Rare Item Detection in e-Commerce Site

Presented at: 18th International World Wide Web Conference (WWW2009)

by Dan Shen, Xiaoyuan Wu, Alvaro Bolivar

Webpage: http://www2009.eprints.org/130/1/p1099.pdf

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-demandintensitive domains show that the method may effectively detect rare items (> 90% precision).

Keywords: Poster Session

Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2009/paper/130

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