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    EFFECTIVE STOCK KEEPING UNIT (SKU) MANAGEMENT SYSTEM
    23.
    发明公开
    EFFECTIVE STOCK KEEPING UNIT (SKU) MANAGEMENT SYSTEM 审中-公开

    公开(公告)号：US20230316353A1

    公开(公告)日：2023-10-05

    申请号：US17712406

    申请日：2022-04-04

    Applicant: ADOBE INC.

    Inventor： Michele Saad ,  Matthew Cecil Zimmerman

    IPC: G06Q30/06 ,  G06F16/22 ,  G06F16/28 ,  H03M7/30

    CPC classification number: G06Q30/0603 ,  G06F16/2272 ,  G06F16/285 ,  H03M7/30

    Abstract: An effective stock keeping unit (SKU) management system encodes catalog data into an embedding per catalog item. An embedding space is created by encoding catalog item data into an embedding per catalog item. The embedding is created by generating an index, where a number of rows represents a number of catalog items and a number of columns represents a number of fields associated with each catalog item. The index is then denormalized using customer groups and transformed by compressing the number of columns, to create the embedding space. In some configuration, a machine learning model is trained using catalog data. In the embedding space, item similarity is encoded by clustering catalog SKUs into groups in the embedding space, by placing similarly related items close to each other in the embedding space. Catalog items are then searched for in the embedding, with the closest clusters searched for a particular catalog item.

    FACILITATING SEARCH RESULT REMOVAL
    24.
    发明公开
    FACILITATING SEARCH RESULT REMOVAL 审中-公开

    公开(公告)号：US20230252027A1

    公开(公告)日：2023-08-10

    申请号：US17666383

    申请日：2022-02-07

    Applicant: ADOBE INC.

    Inventor： Irgelkha Mejia ,  Michele Saad ,  Ronald Eduardo Oribio ,  Robert Burke, Jr.

    IPC: G06F16/2455 ,  G06F16/242 ,  G06F16/248

    CPC classification number: G06F16/24553 ,  G06F16/2445 ,  G06F16/248

    Abstract: The present technology provides for facilitating removal of undesired search results. In one embodiment, a search request including a search term(s) to use for performing a search is obtained. Thereafter, a search query is generated to execute the search. The search query includes the search terms and a removal parameter indicating a particular search result to exclude from search results returned in response to the search request. A set of search results are provided for display via a user device. Such a set of search results can be identified based on execution of the search query and exclude the particular search result.

    DETERMINING CUSTOMIZED CONSUMPTION CADENCES FROM A CONSUMPTION CADENCE MODEL
    25.
    发明公开
    DETERMINING CUSTOMIZED CONSUMPTION CADENCES FROM A CONSUMPTION CADENCE MODEL 审中-公开

    公开(公告)号：US20230186330A1

    公开(公告)日：2023-06-15

    申请号：US17517462

    申请日：2021-11-02

    Applicant: Adobe Inc.

    Inventor： Michele Saad ,  Lauren Dest

    IPC: G06Q30/02 ,  G06Q30/06 ,  G06N3/04

    CPC classification number: G06Q30/0202 ,  G06N3/04 ,  G06Q30/0643

    Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that utilize a consumption cadence model to predict customized consumption cadences for user accounts across a wide variety of consumable items and generate dynamic selectable consumption scheduling options for the consumable items using the customized consumption cadences. For example, the disclosed systems predict a consumption cadence for consuming a consumable item that is customized for a user account that interacted with the consumable item. Additionally, in some embodiments, the disclosed systems utilize collective user behavior from user accounts that are similar to the user account to determine a predicted consumption cadence using a consumption cadence model. After determining such a cadence, in some instances, the disclosed systems also display a dynamic selectable scheduling option within a graphical user interface according to the predicted consumption cadence for the consumable item.

    PREVENTING CONTRAST EFFECT EXPLOITATION IN ITEM RECOMMENDATIONS
    26.
    发明公开
    PREVENTING CONTRAST EFFECT EXPLOITATION IN ITEM RECOMMENDATIONS 审中-公开

    公开(公告)号：US20230142768A1

    公开(公告)日：2023-05-11

    申请号：US17522270

    申请日：2021-11-09

    Applicant: Adobe Inc.

    Inventor： Georgios Theocharous ,  Michele Saad ,  Christopher Nota

    IPC: G06Q30/06 ,  G06K9/62

    CPC classification number: G06Q30/0629 ,  G06Q30/0631 ,  G06K9/6215

    Abstract: An item recommendation system receives a set of recommendable items and a request to select, from the set of recommendable items, a contrast group. The item recommendation system selects a contrast group from the set of recommendable items by applying a recommendation model to the set of recommendable items. The recommendation model includes an item selection model configured to determine an unbiased conversion rate for each item of the set of recommendable items and select a recommended item from the set of recommendable items having a greatest unbiased conversion rate. The recommendation model includes a contrast group selection model configured to select, for the recommended item, a contrast group comprising the recommended item and one or more contrast items. The item recommendation system transmits the contrast group responsive to the request.

    MACHINE LEARNING APPROACHES FOR INTERFACE FEATURE ROLLOUT ACROSS TIME ZONES OR GEOGRAPHIC REGIONS
    27.
    发明申请
    MACHINE LEARNING APPROACHES FOR INTERFACE FEATURE ROLLOUT ACROSS TIME ZONES OR GEOGRAPHIC REGIONS 有权

    公开(公告)号：US20230115855A1

    公开(公告)日：2023-04-13

    申请号：US17500785

    申请日：2021-10-13

    Applicant: Adobe Inc.

    Inventor： Michele Saad ,  Lauren Dest

    IPC: G06N5/02 ,  G06N5/04

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for flexibly and accurately utilizing a machine learning model to intelligently determine and provide interface features for display via client devices located across different time zones or geographic regions. For example, the disclosed systems can utilize a feature visualization machine learning model to generate an arrangement of graphics, an assortment of graphics, or other graphical visualization of one or more interface features in a target time zone (or a target geographic region) based on client device interactions from other (e.g., leading) time zones or geographic regions. In certain embodiments, the disclosed systems also (or alternatively) determine a sequence of geographic regions for rolling out, or surfacing, an interface feature based on similarities between geographic regions and a comparison of performance metrics over multiple candidate sequences.

    Content prediction based on pixel-based vectors
    28.
    发明授权
    Content prediction based on pixel-based vectors 有权

    公开(公告)号：US11615263B2

    公开(公告)日：2023-03-28

    申请号：US17880706

    申请日：2022-08-04

    Applicant: Adobe Inc.

    Inventor： Michele Saad ,  Lauren Dest

    IPC: G06K9/62 ,  G06N3/02 ,  G06F16/538 ,  G06V10/56 ,  G06V10/82

    Abstract: Methods and systems disclosed herein relate generally to systems and methods for predicting content based on vector data structures generated from image pixels. A content-prediction application accesses a color palette having two or more color-palette categories and selects a first color of the color palette. The content-prediction application generates a first vector based on a set of pixel values that represent the first color of the color palette. The content-prediction application determines a distance metric between the first vector and a second vector, in which the second vector is identified by applying a convolutional neural network model on an image depicting an item that includes a second color. In response to determining that the distance metric is less than a predetermined threshold, the content-prediction application selects the content item corresponding to the second vector.

    TEXT ADJUSTED VISUAL SEARCH
    29.
    发明申请
    TEXT ADJUSTED VISUAL SEARCH 有权

    公开(公告)号：US20220138247A1

    公开(公告)日：2022-05-05

    申请号：US17090150

    申请日：2020-11-05

    Applicant: ADOBE INC.

    Inventor： Mikhail Kotov ,  Roland Geisler ,  Saeid Motiian ,  Dylan Nathaniel Warnock ,  Michele Saad ,  Venkata Naveen Kumar Yadav Marri ,  Ajinkya Kale ,  Ryan Rozich ,  Baldo Faieta

    IPC: G06F16/532 ,  G06F16/583 ,  G06F16/538 ,  G06F16/2457

    Abstract: Embodiments of the technology described herein, provide improved visual search results by combining a visual similarity and a textual similarity between images. In an embodiment, the visual similarity is quantified as a visual similarity score and the textual similarity is quantified as a textual similarity score. The textual similarity is determined based on text, such as a title, associated with the image. The overall similarity of two images is quantified as a weighted combination of the textual similarity score and the visual similarity score. In an embodiment, the weighting between the textual similarity score and the visual similarity score is user configurable through a control on the search interface. In one embodiment, the aggregate similarity score is the sum of a weighted visual similarity score and a weighted textual similarity score.

    Recommender System Based On Trendsetter Inference
    30.
    发明申请
    Recommender System Based On Trendsetter Inference 有权

    公开(公告)号：US20210304283A1

    公开(公告)日：2021-09-30

    申请号：US16835986

    申请日：2020-03-31

    Applicant: Adobe Inc.

    Inventor： Michele Saad

    IPC: G06Q30/06 ,  G06N5/04

    Abstract: A trend setting score that identifies a degree of trend setting exhibited by a user is generated for each of multiple users. This degree of trend setting exhibited by the user is an indication of how well the user identifies trends for items (e.g., consumes items) prior to the items becoming popular. The item consumption of users with high trend setting scores is then used to identify items that are expected to become popular after a lag in time. For a given user, another user with a high trend setting score (also referred to as a trendsetter) and having a high affinity with (e.g., similar item consumption behavior or characteristics) the given user is identified. Recommendations are provided to the given user based on items consumed by the trendsetter prior to the items becoming popular.

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