公开(公告)号：US12130809B2

公开(公告)日：2024-10-29

申请号：US17947971

申请日：2022-09-19

Applicant: eBay Inc.

Inventor： Christopher Miller ,  Shubhangi Tandon ,  SenthilKumar Gopal ,  Selcuk Kopru

IPC: G06F16/2453 ,  G06F16/248

CPC classification number: G06F16/24534 ,  G06F16/248

Abstract: A multimodal embedding modifier generates a modified seed search selection embedding for providing a set of search results. The multimodal embedding modifier enhances the ability and accuracy of identifying a user's true intent when searching the online marketplace. For example, embodiments disclosed herein can allow a user to navigate multiple modalities for an item. In some embodiments, a user may select a search result corresponding to an initial search query, and further modify the selected search result by inputting a modifier (e.g., a textual modifier). The multimodal embedding modifier can be trained using a training dataset including a text embedding, an image embedding, another type of embedding, or a combination thereof.

公开(公告)号：US20240265412A1

公开(公告)日：2024-08-08

申请号：US18105483

申请日：2023-02-03

Applicant: eBay Inc.

Inventor： SenthilKumar Gopal

IPC: G06Q30/0202 ,  G06N5/022 ,  G06Q10/087

CPC classification number: G06Q30/0202 ,  G06N5/022 ,  G06Q10/087

Abstract: Systems and methods are directed to automatic listing generation and inventory management based on machine-learning analysis. The system trains a time series-based machine learning (ML) model that forecasts sales. During inference time, the system determines one or more potential categories for a user based on custom preferences and previous analytic queries of the user. High demand items in the one or more potential categories are then applied to the ML model, which outputs probabilities of predicted sales for the high demand items. The system then determines items having a potential inventory gap by cross-checking current inventory with items having a probability outputted by the ML model that satisfies a probability threshold. For each item that satisfies the probability threshold, competitor sales data, predicted sales data derived from the ML model, and editable fields displaying automatic listing thresholds that trigger the automatic generation of a corresponding listing are presented in a user interface.