Rare item detection in e-commerce site

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). Categories and Subject Descriptors H.3.3 [Information Systems ]: Information Search and Retrieval; I.2.6 [Artificial Intelligence]: Learning General Terms Algorithms, Measurement, Performance, Experimentation Keywords long tail theory, rare item detecti...

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: Dan Shen, Xiaoyuan Wu, Alvaro Bolivar
• Keywords: EBay Item Listing, Great Rare Items, Internet Technology, Rare Item Detection, WWW 2009