公开(公告)号：US11699109B2

公开(公告)日：2023-07-11

申请号：US17732249

申请日：2022-04-28

Applicant: Dstillery, Inc.

Inventor： Amelia Grieve White ,  Melinda Han Williams ,  Christopher Allen Jenness ,  Jason Jerard Kaufman ,  Evan Bard Hills ,  Mark Alan Jung

IPC: G06Q30/0201 ,  G06Q30/0251 ,  G06N20/20 ,  G06F16/958 ,  G06F16/955 ,  G06N20/00 ,  G06F18/231 ,  G06N7/01

CPC classification number: G06N20/20 ,  G06F16/955 ,  G06F16/958 ,  G06F18/231 ,  G06N7/01 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0254 ,  G06Q30/0255 ,  G06Q30/0254 ,  G06Q30/0254

Abstract: A computer-implemented method can facilitate delivery of targeted content to user devices in situations in which historic tracking data (e.g., cookie data) is generally unavailable and/or unreliable. A p-dimensional embedding of websites can be generated based on a group of user devices for whom tracking data is available. Conversion event data that indicates indicating whether that audience member performed a conversion action can be received. A machine learning model can be trained using the conversion event data and the positions of websites appearing in the conversion event data within the p-dimensional embedding to predict a likelihood of conversion and/or a type of content to provide given a position in the p-dimensional embedding. When an indication that a user device is accessing a website is received, a position of that website in the p-dimensional embedding can be determined and targeted content can be delivered to the user device.

公开(公告)号：US11068935B1

公开(公告)日：2021-07-20

申请号：US17108770

申请日：2020-12-01

Applicant: Dstillery, Inc.

Inventor： Amelia Grieve White ,  Melinda Han Williams ,  Christopher Allen Jenness ,  Jason Jerard Kaufman

IPC: G06Q30/02 ,  G06K9/62 ,  G06N20/00

Abstract: A computer-implemented method can facilitate delivery of targeted content to user devices in situations in which historic tracking data (e.g., cookie data) is generally unavailable and/or unreliable. A p-dimensional embedding of websites can be generated based on a group of user devices for whom tracking data is available. Conversion event data that indicates indicating whether that audience member performed a conversion action can be received. A machine learning model can be trained using the conversion event data and the positions of websites appearing in the conversion event data within the p-dimensional embedding to predict a likelihood of conversion and/or a type of content to provide given a position in the p-dimensional embedding. When an indication that a user device is accessing a website is received, a position of that website in the p-dimensional embedding can be determined and targeted content can be delivered to the user device.

公开(公告)号：US12182723B2

公开(公告)日：2024-12-31

申请号：US18310018

申请日：2023-05-01

Applicant: Dstillery, Inc.

Inventor： Jason Jerard Kaufman ,  Amelia Grieve White ,  Christopher Allen Jenness ,  Mark Alan Jung ,  Melinda Han Williams

IPC: G06N3/09 ,  G06Q30/0242 ,  G06Q30/0273

Abstract: A method includes accessing web browsing history for a plurality of users, generating embedding vectors based on the web browsing history for websites, and selecting a model configured to receive embedding vectors and output probability of a conversion events. Further, the method includes calculating a probability of a conversion event for the various websites using the model, selecting a subset of websites from the various websites based on websites having associated probabilities greater that a predetermined probability threshold, and receiving an indication that an impression has been displayed to a user when the user visits a website from the subset of websites, obtaining a plurality of conversion rates, each conversion rate is determined for each website from the subset of websites based on a number of conversion events associated with the plurality of visitation events, and updating the model parameters of the model using the obtained plurality of conversion rates.

公开(公告)号：US12045703B2

公开(公告)日：2024-07-23

申请号：US17569412

申请日：2022-01-05

Applicant: Dstillery, Inc.

Inventor： Amelia Grieve White ,  Melinda Han Williams ,  Christopher Allen Jenness ,  Jason Jerard Kaufman ,  Evan Bard Hills ,  Mark Alan Jung

IPC: G06Q30/0201 ,  G06F16/955 ,  G06F16/958 ,  G06F18/231 ,  G06N7/01 ,  G06N20/00 ,  G06N20/20 ,  G06Q30/0251

CPC classification number: G06N20/20 ,  G06F16/955 ,  G06F16/958 ,  G06F18/231 ,  G06N7/01 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0254 ,  G06Q30/0255 ,  G06Q30/0254 ,  G06Q30/0254

Abstract: A computer-implemented method can facilitate delivery of targeted content to user devices in situations in which historic tracking data (e.g., cookie data) is generally unavailable and/or unreliable. A p-dimensional embedding of websites can be generated based on a group of user devices for whom tracking data is available. Conversion event data that indicates indicating whether that audience member performed a conversion action can be received. A machine learning model can be trained using the conversion event data and the positions of websites appearing in the conversion event data within the p-dimensional embedding to predict a likelihood of conversion and/or a type of content to provide given a position in the p-dimensional embedding. When an indication that a user device is accessing a website is received, a position of that website in the p-dimensional embedding can be determined and targeted content can be delivered to the user device.