TY  - CONF
ID  - www2009130
UR  - http://www2009.eprints.org/130/
A1  - Shen, Dan
A1  - Wu, Xiaoyuan
A1  - Bolivar, Alvaro
Y1  - 2009/04//
N2  - 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 ?nd 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 ?lter 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).
TI  - Rare Item Detection in e-Commerce Site
SP  - 1099
M2  - Madrid, Spain
AV  - public
EP  - 1099
T2  - 18th International World Wide Web Conference
ER  -