GENERATIVE ARTIFICIAL INTELLIGENCE SECURITY ENGINE IN AN ITEM LISTING SYSTEM

    公开(公告)号:US20250150474A1

    公开(公告)日:2025-05-08

    申请号:US18502606

    申请日:2023-11-06

    Applicant: eBay Inc.

    Abstract: Methods, systems, and computer storage media for providing generative artificial intelligence (AI) security management using a generative AI security engine in an item listing system. A generative AI security engine supports generative AI security management based on security analysis and detection operations for a plurality of generative-AI-supported applications and generative AI models. In operation, a request associated with prompt data is communicated from a generative AI client. Based on communicating the request, a response that is generated based on a redacted version of the prompt data is received at the generative AI client. The prompt data is analyzed using a plurality of security engine operations to cause generation of the redacted version of the prompt data. The redacted version of the prompt data is used to generate the response at a generative AI model. The response is caused to be generated at an interface associated with the generative AI client.

    Complementary item recommendation system

    公开(公告)号:US12288238B2

    公开(公告)日:2025-04-29

    申请号:US17830641

    申请日:2022-06-02

    Applicant: eBay Inc.

    Abstract: A recommendation system leverages multi-target search to provide item listing recommendations and/or query suggestions. For a given input image with multiple objects, multi-target search uses object detection to detect each object, and stores complementary object data associating each object from the image. Additionally, a search of an item listing datastore is performed using each object from the image as a search query. Based on item listings returned as search results, complementary item listings data associating item listings is stored. In some configurations, the complementary item listings data is also used to train a machine learning model to predict complementary item listings for a given item listing. When an input item listing is received, item listing recommendations and/or query suggestions are determined for the input item listing using the complementary object data, the complementary item listing data, and/or the machine learning model.

    BI-DIRECTIONAL PROJECT INFORMATION UPDATES IN MULTI-PARTY BIDDING

    公开(公告)号:US20250124500A1

    公开(公告)日:2025-04-17

    申请号:US18999929

    申请日:2024-12-23

    Applicant: eBay inc.

    Abstract: In an example embodiment, bid specifications for an ecommerce transaction are transmitted from a party requesting bids to a plurality of bidders. Then a modification to the bid specifications is received from a first bidder of the plurality of bidders along with a bid in accordance with the modified bid specifications. The modified bid specifications may then be transmitted to the plurality of bidders other than the first bidder. Bids in accordance with the modified bid specifications are then received from each of the plurality of bidders other than the first bidder. One of the bids may be selected, and the ecommerce transaction may be consummated based on the selected bid.

    INTERACTIVE PRODUCT REVIEW INTERFACE

    公开(公告)号:US20250124494A1

    公开(公告)日:2025-04-17

    申请号:US19000176

    申请日:2024-12-23

    Applicant: eBay Inc.

    Abstract: Systems and methods for creating and presenting interactive product review interfaces are presented. The system processes a purchase request for a product from a user. The system then identifies one or more user feedback questions for the product. For each particular user feedback question, the system generates user feedback graphics based on stored user feedback associated with the particular user feedback question. The system transmits the one or more selected user feedback questions and the generated user feedback graphics to a client system associated with the user for display. The system receives user feedback for a user feedback question in the selected one or more user feedback questions. The system updates the user feedback graphic associated with the question to include the received user feedback. The system transmits the updated user feedback graphic to the client system for display in real-time.

    PIVOT GROUP GENERATION FOR SEARCH AND RECOMMENDATION SYSTEMS

    公开(公告)号:US20250124483A1

    公开(公告)日:2025-04-17

    申请号:US18399452

    申请日:2023-12-28

    Applicant: eBay Inc.

    Abstract: Some aspects relate to technologies for generating pivots using a generative model and grouping items into pivot groups using the pivots. Pivots are generated by obtaining item information for items, generating a prompt using the item information, and causing a generative model to use the prompt to generate text for the pivots, including a pivot name and pivot description for each pivot. A pivot embedding is also generated for each pivot. When items are to be returned to a user device (e.g., as recommended items or search result items), item embeddings for the items and the pivot embeddings for the pivots are used to assign each item to a particular pivot to generate pivot groups that each includes a pivot name, a pivot description, and assigned items. User interface information is provided to present at least a portion of the pivot groups on a user device.

    SYSTEMS AND METHODS FOR ON DEMAND LOCAL COMMERCE

    公开(公告)号:US20250117819A1

    公开(公告)日:2025-04-10

    申请号:US18983246

    申请日:2024-12-16

    Applicant: eBay Inc.

    Abstract: Systems and methods for on demand local commerce are described. One example embodiment includes a device gathering location information and product interest associated with clients and client devices. The system may use location information in determining that the first plurality of client devices are within a first geographic area during a first time period, and may further use the interest information in calculating an interest level for a first product. A threshold may be identified and used in determining that the interest level for the first product exceeds the threshold. When the calculated interest level exceeds the threshold, a local commerce action is initiated. In various embodiments, the local commerce action may be a live on demand auction at a particular location, an offer associated with a geofenced area, a sales location recommendation to a merchant, or any other such local commerce action.

    Reconstruction of 3D model with immersive experience

    公开(公告)号:US12260509B2

    公开(公告)日:2025-03-25

    申请号:US18216583

    申请日:2023-06-29

    Applicant: eBay Inc.

    Abstract: A system receives image data associated with an item, where the image data comprising a view of the item from two or more angles; determines physical attributes of the item; generates a base model of the item; samples the base model to generate one or more sampled models, each of the one or more sampled models comprising a subset of the geometric data, the subset of the geometric data determined based on one or more device characteristics of one or more user devices that interface with the system; receives device characteristics of a user device associated with a request from the user device for the item; selects, based on the received device characteristics, a sampled model of the item; and transmits a data object comprising the selected sampled model to the user device to cause the user device to generate a three-dimensional rendering of the item.

    DETECTING OUTLIERS IN MULTIMODAL DISTRIBUTIONS USING EMPIRICAL CUMULATIVE DISTRIBUTION FUNCTIONS

    公开(公告)号:US20250088523A1

    公开(公告)日:2025-03-13

    申请号:US18652151

    申请日:2024-05-01

    Applicant: eBay Inc.

    Abstract: A method for detecting an anomaly is provided. The method receives and organizes data as a function of a plurality of time periods and a number of updates for each time period of the plurality of time periods. The organized data approximates first and second unimodalities. The first and second unimodalities have respective first and second peaks. The method identifies a dip across the plurality of time periods and determines a density of the dip. The density is compared with a predetermined threshold in order to determine if the dip is an alternative modality. A unimodality analysis is then performed on the first and second unimodalities in response to the dip being an alternative modality. The method also determines whether the second unimodality is an anomaly based on the unimodality analysis and discards the updates associated with the second unimodality when the second unimodality is an anomaly.

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