公开(公告)号：US20170337612A1

公开(公告)日：2017-11-23

申请号：US15162129

申请日：2016-05-23

Applicant: eBay Inc.

Inventor： Daniel Galron ,  Siming Li ,  Krutika Shetty

IPC: G06Q30/06

CPC classification number: G06Q30/0631 ,  G06Q30/0641

Abstract: A system and method to evaluate the affinity of a collection of sale items to a user's interests. The affinity is a measure of how closely a user's interests match the contents of a collection (e.g., a collection of items selected by a seller, other user, or employee of the sales site). The method may determine the affinity of various collections by using a vector-space distance measure between the user's categories of interest and the relative percentages of various categories of items in each collection's. The method may also add a quality score for the collection to the affinity score and/or a random value to ensure that the system recommends high quality collections does not recommend the same set of collections every time the user logs in or visits the sales site.

公开(公告)号：US20170293695A1

公开(公告)日：2017-10-12

申请号：US15190279

申请日：2016-06-23

Applicant: eBay Inc.

Inventor： Yuri Michael Brovman ,  Marie Jacob ,  Natraj Srinivasan ,  Stephen Neola ,  Daniel Galron ,  Ryan Snyder ,  Paul Wang

IPC: G06F17/30

CPC classification number: G06Q30/0631 ,  G06Q30/0251

Abstract: Systems, methods and media are provided for optimizing similar item recommendations in a semi-structured environment. In one embodiment a system includes at least one processor and a memory storing instructions that, when executed by the at least one processor, cause the system to perform operations comprising, at least identifying a seed item; retrieving a subset of recommended items relevant to the seed item; and ranking the subset of recommended items based on an item conversion probability, wherein the ranking of the subset of recommended items is based on a machine learning technique, and wherein a binary or multi-class label is used as training input to the machine learning technique.