Goran Predovic

US Patent:

20130038540, Feb 14, 2013

Filed:

Aug 12, 2011

Appl. No.:

13/209058

Inventors:

Jen Anderson - Kirkland WA, US
Eric Christian Brown - Seattle WA, US
Jennifer Teed - Redmond WA, US
Goran Predovic - Redmond WA, US
Bruce Edward James - Shoreline WA, US
Fei Su - Issaquah WA, US
Maybelle Lippert - Redmond WA, US
Mudit Agrawal - Redmond WA, US

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G06F 3/041

US Classification:

345173

Abstract:

User inputs can indicate an intent of a user to target a location on a display. In order to determine a targeted point based on a user input, a computing device can receive an indication of at least one point, an indication of a width, and an indication of a height. The computing device can estimate a portion of the display based on the indication of the at least one point, the indication of the width, and the indication of the height. The computing device can also determine the targeted point based on a location of the at least one point and based on a location of a portion of one or more objects within the estimated portion of the display.

US Patent:

20180314880, Nov 1, 2018

Filed:

Apr 26, 2017

Appl. No.:

15/497454

Inventors:

- Menlo Park CA, US
Li Zhou - Campbell CA, US
Yimin Song - Sunnyvale CA, US
Goran Predovic - Redmond WA, US
Chaochao Cai - Bellevue WA, US
Liang Xu - Bellevue WA, US

International Classification:

G06K 9/00
G06F 17/28
G06K 9/62
G06F 17/30
H04L 12/58

Abstract:

An online system matches a user across multiple online systems based on image data for the user (e.g., profile photo) regardless whether the image data is from the online system, a different but related online system or a third party system. For example, to match the user across a social networking system and INSTAGRAM™ system, the online system compares the similarity between images of the user from both systems in addition to similarity of textual information in the user profiles on both systems. The similarity of image data and the similarity of textual information associated with the user are used by the online system as indicators of matched user accounts belonging to the same user across both systems. The online system applies models trained using deep learning techniques to match a user across multiple online systems based on the image data and textual information associated with the user.

US Patent:

20180314915, Nov 1, 2018

Filed:

Apr 26, 2017

Appl. No.:

15/497866

Inventors:

- Menlo Park CA, US
Goran Predovic - Redmond WA, US
Wei Wei - Fremont CA, US
Chang Liu - Foster City CA, US
Liang Xu - Bellevue WA, US

International Classification:

G06K 9/62
G06N 99/00
G06N 5/04
G06K 9/00
G06K 9/66
G06K 9/72

Abstract:

An online system predicts gender, age, interests, or other demographic information of a user based on image data of the user, e.g., profile photos, photos the user posts of him/herself within an online system, and photos of the user posted by other users socially connected with the user, and textual data in the user's profile that suggests age or gender (e.g., like or dislikes similar to a population of users of an online system). The online system similarly predicts a user's interests based on the photos of the user. The online system applies one or more models trained using deep learning techniques to generate the predictions. The online system uses the predictions to build more information about the user in the online system, and provide improved and targeted content delivery to the user that may have disparate information scattered throughout different online systems.

US Patent:

20180204133, Jul 19, 2018

Filed:

Jan 18, 2017

Appl. No.:

15/409374

Inventors:

- Menlo Park CA, US
Goran Predovic - Redmond WA, US

International Classification:

G06N 99/00
G06F 17/30
H04L 29/08

Abstract:

Disclosed is a content sharing system that infers demographic attributes of users of the content sharing system based on features of the users with accounts matched to an online system with known demographic attributes. The features include attributes of unidirectional connections of the users on the content sharing system. In some embodiments, the features are distributions of demographic attributes of the unidirectional connections of the users, such as distributions of ages or genders of the unidirectional connections. The content sharing system provides the features as input to a classifier trained to predict a particular demographic attribute value and the classifier outputs a predicted value of that demographic attribute. In some embodiments, the content sharing system trains a classifier for various demographic attributes by forming training sets for the demographic attributes using the features for users.

US Patent:

20180204230, Jul 19, 2018

Filed:

Jan 17, 2017

Appl. No.:

15/408121

Inventors:

- Menlo Park CA, US
Goran Predovic - Redmond WA, US

International Classification:

G06Q 30/02
G06N 99/00

Abstract:

Disclosed is an online system that infers demographic attributes of unresolved users for whom the demographic attributes are not known. The online system determines certain features about devices used by the unresolved users, but does not have certain information about the users themselves (e.g., their age, gender, or location), so instead infers these attributes based on the features of the user devices. The online system provides the features about the devices as input to a classifier trained to predict a particular demographic attribute value, and the classifier outputs a prediction of whether the user of the user device has the corresponding value of the demographic attribute. In one embodiment, the online system trains a classifier for various demographic attribute values by forming training sets for the demographic attribute values using the features of devices for users who are logged into the online system and hence have known demographic attribute values.

US Patent:

20180060753, Mar 1, 2018

Filed:

Aug 29, 2016

Appl. No.:

15/250452

Inventors:

- Menlo Park CA, US
Chaochao Cai - Bellevue WA, US
Goran Predovic - Redmond WA, US

International Classification:

G06N 99/00
H04L 29/08

Abstract:

An online system obtains a set of resolved impressions based on historical data about multiple publishers. A set of features is then extracted, for each resolved impression, based on a comparison of historical data about the first publisher and the second publisher. The online system performs training of a machine-learned model based on the set of features. Data about a plurality of new impressions are input into the trained machine-learned model to obtain an output of the trained machine-learned model. A reach overlap metric and unique reach metric can be computed based on the output of the trained machine-learned model.