公开(公告)号：US20220237226A1

公开(公告)日：2022-07-28

申请号：US17687773

申请日：2022-03-07

Applicant: Spotify AB

Inventor： James E. McInerney ,  Benjamin Lacker ,  Samantha Hansen ,  Aloïs Gruson ,  Rishabh Mehrotra ,  Hugues Bouchard

IPC: G06F16/635 ,  G06K9/62 ,  G06F16/638

Abstract: Methods, systems and computer program products are provided personalizing recommendations of items with associated explanations. The example embodiments described herein use contextual bandits to personalize explainable recommendations (“recsplanations”) as treatments (“Bart”). Bart learns and predicts satisfaction (e.g., click-through rate, consumption probability) for any combination of item, explanation, and context and, through logging and contextual bandit retraining, can learn from its mistakes in an online setting.

公开(公告)号：US20200012681A1

公开(公告)日：2020-01-09

申请号：US16502975

申请日：2019-07-03

Applicant: Spotify AB

Inventor： James E. McInerney ,  Benjamin Lacker ,  Samantha Hansen ,  Aloïs Gruson ,  Rishabh Mehrotra

IPC: G06F16/635 ,  G06F16/638 ,  G06K9/62

Abstract: Methods, systems and computer program products are provided personalizing recommendations of items with associated explanations. The example embodiments described herein use contextual bandits to personalize explainable recommendations (“recsplanations”) as treatments (“Bart”). Bart learns and predicts satisfaction (e.g., click-through rate, consumption probability) for any combination of item, explanation, and context and, through logging and contextual bandit retraining, can learn from its mistakes in an online setting.

公开(公告)号：US11782968B2

公开(公告)日：2023-10-10

申请号：US16789214

申请日：2020-02-12

Applicant: Spotify AB

Inventor： Casper Hansen ,  Christian Hansen ,  Lucas Maystre ,  Rishabh Mehrotra ,  Brian Christian Peter Brost ,  Federico Tomasi ,  Mounia Lalmas-Roelleke

IPC: G06F16/435 ,  G06F16/438 ,  G06F16/41 ,  H04L65/60 ,  G06N3/08 ,  G06F16/2457

CPC classification number: G06F16/435 ,  G06F16/24575 ,  G06F16/41 ,  G06F16/438 ,  G06N3/08 ,  H04L65/60

Abstract: An electronic device stores a plurality of vector representations for respective media content items in a vector space, where each vector represents a media content item. The electronic device receives a first set of input parameters representing a previous session of a user of the media-providing service where the previous session included two or more of the respective media content items. The electronic device then receives a second set of input parameters representing a current context of the user and provides the first set of input parameters and the second set of input parameters to a neural network to generate a prediction vector for a current session. The prediction vector is embedded in the vector space. The electronic device identifies, based on the prediction vector for the current session, a plurality of media content items of the respective media content items in the vector space and provides the plurality of media content items to the user of the media-providing service during the current session.

公开(公告)号：US11556828B2

公开(公告)日：2023-01-17

申请号：US17170543

申请日：2021-02-08

Applicant: Spotify AB

Inventor： Rishabh Mehrotra ,  Niannan Xue ,  Mounia Lalmas-Roelleke

IPC: G06F3/048 ,  G06N7/00 ,  G06F9/451 ,  G06F3/0482

Abstract: An electronic device for a first session of a user, for each of a plurality of lists of media content items, determines a respective value for each objective of a first set of objectives and a second set of objectives by accessing contextual data for the first session of the user. The first set of objectives corresponds to the user and the second set of objectives corresponds to a second party distinct from the user. The electronic device, using a multi-arm bandit model, identifies a first list of media content items, from the plurality of lists of media content items, to present to the user, including: calculating a score for each list in the plurality of lists of media items; and probabilistically selecting the first list of media content items according to the respective scores corresponding to the respective lists in the plurality of lists of media items.

公开(公告)号：US20220012565A1

公开(公告)日：2022-01-13

申请号：US17320439

申请日：2021-05-14

Applicant: Spotify AB

Inventor： Christian Hansen ,  Casper Hansen ,  Brian Christian Peter Brost ,  Lucas Maystre ,  Mounia Lalmas-Roelleke ,  Rishabh Mehrotra

IPC: G06N3/04 ,  G06N3/08

Abstract: A reinforcement learning ranker can take into account previously-recommended media content items to produce a ranked list of media content items to recommend next. The ranker finds a policy that gives the probability of sampling a media content item given a state. The policy is learned such that it maximizes a reward. A reward function associated with the media content item can be defined with respect to whether the user finds the media content item relevant (likelihood that the user will like the media content item) and a diversity score of the media content item.

公开(公告)号：US20230376529A1

公开(公告)日：2023-11-23

申请号：US18331245

申请日：2023-06-08

Applicant: Spotify AB

Inventor： James E. McInerney ,  Benjamin Lacker ,  Samantha Hansen ,  Aloïs Gruson ,  Rishabh Mehrotra ,  Hugues Bouchard

IPC: G06F16/635 ,  G06F16/638 ,  G06F18/21

CPC classification number: G06F16/637 ,  G06F16/639 ,  G06F18/217

Abstract: Methods, systems and computer program products are provided personalizing recommendations of items with associated explanations. The example embodiments described herein use contextual bandits to personalize explainable recommendations (“recsplanations”) as treatments (“Bart”). Bart learns and predicts satisfaction (e.g., click-through rate, consumption probability) for any combination of item, explanation, and context and, through logging and contextual bandit retraining, can learn from its mistakes in an online setting.

公开(公告)号：US11544315B2

公开(公告)日：2023-01-03

申请号：US17075305

申请日：2020-10-20

Applicant: Spotify AB

Inventor： Rishabh Mehrotra ,  Harpreet Singh ,  Madaline Minuet Kirwin ,  Edward Lee ,  Adam Latour Piel

IPC: G06F16/438 ,  G06F17/18 ,  G06N20/00

Abstract: An electronic device, for each media content item of a plurality of media content items, receives a respective score for each of a first set of objectives and a second set of objectives and generates a respective score between a user and the media content item. The generating includes applying a first ordered weighted average to the respective scores for the first set of objectives, to produce a first combined score for the first set of objectives, applying a second ordered weighted average to the respective scores for the second set of objectives, to produce a second combined score for the second set of objectives and applying a third ordered weighted average to the combined score for the first set of objectives and the second set of objectives. The electronic device provides media content to the user based on the respective scores between the user and the media content items.

公开(公告)号：US20220092118A1

公开(公告)日：2022-03-24

申请号：US17027239

申请日：2020-09-21

Applicant: Spotify AB

Inventor： Federico Tomasio ,  Rishabh Mehrotra ,  Brian Christian Peter Brost ,  Aasish Kumar Pappu ,  Hugo Flávio Ventura Galvão ,  Mounia Lalmas-Roelleke

IPC: G06F16/9035 ,  G06F16/9038 ,  G06K9/62 ,  G06N3/04 ,  G06N5/02

Abstract: Methods, systems and computer program products are provided for query understanding. A non-focused query quantifier generates non-focused query features that quantify a non-focused query and a non-focused query predictor generates a prediction associated with the non-focused query based on the non-focused query features.

公开(公告)号：US11853344B2

公开(公告)日：2023-12-26

申请号：US18145809

申请日：2022-12-22

Applicant: Spotify AB

Inventor： Rishabh Mehrotra ,  Harpreet Singh ,  Madaline Minuet Kirwin ,  Edward Lee ,  Adam Latour Piel

IPC: G06F16/438 ,  G06F17/18 ,  G06N20/00

CPC classification number: G06F16/4387 ,  G06F17/18 ,  G06N20/00

Abstract: An electronic device, for each media content item of a plurality of media content items, receives a respective score for each a first set of objectives and one or more other objectives and generates a respective score between a user and the media content item. The generating includes applying a first ordered weighted average to the respective scores for the first set of objectives, to produce a first combined score for the first set of objectives, applying a second ordered weighted average to the respective scores for a second set of objectives, wherein the second set of objectives includes (i) a resulting objective corresponding to the first set of objectives and having the first combined score and (ii) the one or more other objectives. The electronic device streams media content to the user selected based on the respective scores between the user and the media content items.

公开(公告)号：US11709886B2

公开(公告)日：2023-07-25

申请号：US17687773

申请日：2022-03-07

Applicant: Spotify AB

Inventor： James E. McInerney ,  Benjamin Lacker ,  Samantha Hansen ,  Alois Gruson ,  Rishabh Mehrotra ,  Hugues Bouchard

IPC: G06F16/00 ,  G06F16/635 ,  G06F16/638 ,  G06F18/21

CPC classification number: G06F16/637 ,  G06F16/639 ,  G06F18/217

Abstract: Methods, systems and computer program products are provided personalizing recommendations of items with associated explanations. The example embodiments described herein use contextual bandits to personalize explainable recommendations (“recsplanations”) as treatments (“Bart”). Bart learns and predicts satisfaction (e.g., click-through rate, consumption probability) for any combination of item, explanation, and context and, through logging and contextual bandit retraining, can learn from its mistakes in an online setting.