公开(公告)号：US20210049674A1

公开(公告)日：2021-02-18

申请号：US16543500

申请日：2019-08-16

Applicant: eBay Inc.

Inventor： Ramesh PERIYATHAMBI ,  Manojkumar Rangasamy KANNADASAN ,  Lakshimi DURAIVENKATESH ,  Tomer LANCEWICKI ,  Selcuk KOPRU

IPC: G06Q30/06 ,  G06F9/451 ,  G06F16/955 ,  G06N20/00

Abstract: The disclosed technologies include receiving a selection of an item, where the item has a plurality of selectable configurations. Feature data that is associated with the item is accessed. The feature data includes product information and a purchase history for the plurality of selectable configurations for the item. Based on the feature data, one or more of the selectable configurations are predicted to be of interest to a user associated with the selection. A user interface including the predicted configurations with the feature data is rendered.

公开(公告)号：US20220156175A1

公开(公告)日：2022-05-19

申请号：US16952721

申请日：2020-11-19

Applicant: eBay Inc.

Inventor： Ramesh PERIYATHAMBI ,  Tomer LANCEWICKI ,  Senthil Kumar PADMANABHAN ,  Srikanth RENTACHINTALA ,  Kandakumar DORAISAMY

IPC: G06F11/36 ,  G06F21/62 ,  G06F16/22 ,  G06Q30/06 ,  G06Q10/06 ,  G06N20/00 ,  G06N5/04 ,  G06F40/40

Abstract: A first test case identifier that indicates a first test case is received. The first test case is indicative of testing one or more features of an application associated with the electronic marketplace. The first test case identifier is compared to a plurality of attributes. The plurality of attributes are associated with one or more listings that describe one or more items for sale in an electronic marketplace. Based at least in part on the comparing, it is determined that a first set of attributes, of the plurality of attributes, are test data candidates to be used as input to the first test case. Based at least in part on the determining, the first test case is caused to be run using at least one of the first set of attributes as test data for input.

公开(公告)号：US20230388362A1

公开(公告)日：2023-11-30

申请号：US18450246

申请日：2023-08-15

Applicant: eBay Inc.

Inventor： Vineet BINDAL ,  Naga Sita Raghuram NIMISHAKAVI VENKATA ,  Ramesh PERIYATHAMBI ,  Lakshimi DURAIVENKATESH ,  Tomer LANCEWICKI ,  Selcuk KOPRU

IPC: H04L67/02 ,  H04L9/40 ,  G06F16/95 ,  H04L67/01

CPC classification number: H04L67/02 ,  H04L63/0807 ,  G06F16/95 ,  H04L67/01

Abstract: Systems and methods for processing webpage calls via multiple module responses are described. A system may receive, from a client device, a first call for module data associated with a set of webpage modules for presentation in a webpage. The system may subsequently transmit, to the client device based on receiving the first call, a first response including first module data associated with a first subset of the set of webpage modules. The first response may additionally include a token identifying the webpage. The server may additionally transmit, to the client device based on transmitting the first response, a second response including the token identifying the webpage and second module data associated with a second subset of the set of webpage modules that differs from the first subset of the set of webpage modules.

公开(公告)号：US20220309552A1

公开(公告)日：2022-09-29

申请号：US17214242

申请日：2021-03-26

Applicant: eBay Inc.

Inventor： Tomer LANCEWICKI ,  Sanjika HEWAVITHARANA ,  Bindia SARAF ,  Vanuj JUNEJA ,  Dhaval D KARWA

IPC: G06Q30/06 ,  G06N5/04 ,  G06Q50/00 ,  G06Q10/08 ,  G06Q30/02

Abstract: Technologies are shown for artificial intelligence agents for predicting items of interest utilizing multiple data sources, such as historical user behavior, item wear profiles, inventory data and social network data. User models to the multiple sources of data to predict an item of interest to the user. Search requests pertaining to the predicted item can be generated and submitted to electronic commerce platforms and results responsive to the first set of search requests pertaining to the first predicted item received. In one aspect, one or more of the search results can be selected for display to the user. A search result selected by the user can be received and a purchase transaction committed. In another aspect, the agent is authorized to autonomously execute a purchase transaction on a selected one of the search results. Different model types can be utilized for predicting different types of items.

公开(公告)号：US20210042811A1

公开(公告)日：2021-02-11

申请号：US16659092

申请日：2019-10-21

Applicant: eBay Inc.

Inventor： Tomer LANCEWICKI ,  Selcuk KOPRU

IPC: G06Q30/06 ,  G06N20/00 ,  G06N3/04 ,  G06F40/58 ,  G06F17/16

Abstract: Techniques are disclosed for automatically adjusting machine learning parameters in an e-commerce system. Hyperparameters of a machine learning component are tuned using a gradient estimator and a first training set representative of an e-commerce context. The machine learning component is trained using the tuned hyperparameters and the first training set. The hyperparameters are automatically re-tuned using the gradient estimator and a second training set representative of a changed e-commerce context. The machine learning component is re-trained using the re-tuned hyperparameters and the second training set.