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公开(公告)号：US20210294717A1
公开(公告)日：2021-09-23
申请号：US17209633
申请日：2021-03-23
Applicant: eBay Inc.
Inventor： Hanzhang WANG , Huai JIANG , Liangfei SU , Selcuk KOPRU , Sanjeev KATARIYA , Wanxue LI
Abstract: Technologies are shown for generating process flow graphs from system trace data that involve obtaining raw distributed trace data for a system, aggregating the raw distributed trace data into aggregated distributed trace data, generating a plurality of process flow graphs from the aggregated distributed trace data, and storing the plurality of process flow graphs in a graphical store. A first critical path can be determined from the plurality of process flow graphs based on an infrastructure design for the system and a process flow graph corresponding to the first critical path provided for graphical display. Certain examples can determine a second critical path involving a selected element of the first critical path and provide the process flow graph for the second critical path for display. Some examples pre-process the aggregated distributed trace data to repair incorrect traces. Other examples merge included process flow graphs into longer graphs.
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公开(公告)号：US20230385175A1
公开(公告)日：2023-11-30
申请号：US18232525
申请日：2023-08-10
Applicant: eBay Inc.
Inventor： Hanzhang WANG , Huai JIANG , Liangfei SU , Selcuk KOPRU , Sanjeev KATARIYA , Wanxue LI
CPC classification number: G06F11/3476 , G06F11/3409 , G06N20/00 , G06F11/0772 , G06F11/323
Abstract: Technologies are shown for generating process flow graphs from system trace data that involve obtaining raw distributed trace data for a system, aggregating the raw distributed trace data into aggregated distributed trace data, generating a plurality of process flow graphs from the aggregated distributed trace data, and storing the plurality of process flow graphs in a graphical store. A first critical path can be determined from the plurality of process flow graphs based on an infrastructure design for the system and a process flow graph corresponding to the first critical path provided for graphical display. Certain examples can determine a second critical path involving a selected element of the first critical path and provide the process flow graph for the second critical path for display. Some examples pre-process the aggregated distributed trace data to repair incorrect traces. Other examples merge included process flow graphs into longer graphs.
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公开(公告)号：US20220319551A1
公开(公告)日：2022-10-06
申请号：US17223672
申请日：2021-04-06
Applicant: eBay Inc.
Inventor： Antonio HARO , Ellis Shui-Man LUK , Selcuk KOPRU
IPC: G11B27/036 , G10L13/04 , G06F16/683 , G06F21/10 , G06Q30/06 , G06N3/08
Abstract: A video is provided to viewers using a web-based platform without restricted audio, such as a copyrighted soundtrack. To do so, a video comprising at least two audio layers is received. The audio layers can include separate and distinct audio layers or a mix of audio from separate sources. A restricted audio element is identified in a first audio layer and a speech element is identified in a second audio layer. A stitched text string can be generated by performing speech-to-text on both audio layers and removing the text corresponding to the restricted audio element of the second audio layer. When playing back the video, a portion of the video is muted based on the restricted audio element. A voice synthesizer is employed to generate audible sound during the muted portion using the stitched text string.
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Patent Agency Ranking
公开(公告)号：US20230101174A1
公开(公告)日：2023-03-30
申请号：US17587698
申请日：2022-01-28
Applicant: eBay Inc.
Inventor： Selcuk KOPRU , Santosh SHAHANE , Pavel PETRUSHKOV , Friedrich Leonard DAHLMANN , Michael Damian KOZIELSKI
Abstract: Systems and methods provide determining listings of items based on similarities at least among items and queries in an online shopping system. In particular, the systems and methods determine similarities among items, users, product, messages, reviews, and queries, based on a combination of a machine learning model and similarity index data. The machine learning model (e.g., a Transformer model and a neural network model) generates embedded vector representation of items, queries, and other data in the online shopping systems. The machine learning model may be pre-trained based at least on data associated with items in the online shopping system, and fine-tuned based on a variety of mappings of similarities: item-to-item, user-to-item, query-to-item, and the like. The similarity index data include k-Nearest Neighbor index data for determining items within a range of similarity based on a receive query.
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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.
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公开(公告)号：US20250053999A1
公开(公告)日：2025-02-13
申请号：US18921993
申请日：2024-10-21
Applicant: eBay Inc.
Inventor： Selcuk KOPRU , Ellis Shui-Man LUK
IPC: G06Q30/018 , G06F18/22 , G06N5/04 , G06N20/00 , G06Q30/0601 , G06V20/40
Abstract: Various methods and systems for providing indications of inconsistent attributes of item listings associated in item listing videos. An item listing video—of an item listing—is accessed. The item listing video is accessed via an item listing interface of an item listing system. Extracted item features—via a machine learning engine—of an item from the item listing video, are accessed. The extracted item features are extracted based on listing-interface item features associated with listing the item. The extracted item features of the item are compared to the listing-interface item features of the item. Based on comparing the listing-interface item features to the extracted, an inconsistent attribute—between an extracted item feature and a listing-interface item feature that is associated with listing the item—is identified. An indication of an inconsistent attribute is communicated to cause display of the indication of the inconsistent attribute at the item listing interface.
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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
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.
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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
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.
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