Apple Inc.

Pinterest, Inc.

Andrew Liu Chen

Wei Guang Wu

Mukund Narasimhan

Lance Alan Riedel

Walton Fong

Sonja Sabina Knoll

Vitaliy Kulikov

Xuefeng Wang

Sung Chang Lee

Chao Wang

Ki Myung Lee

Siyang Xie

Richard J Blanco

Cheng-I Lin

Jiacheng Hong

Eric Shi

Zheng Liu

Kenneth H Mahan

Kyle B Cruz

Maxime Chevreton

Benjamin W Bylenok

Cole Timothy Rottweiler

Alan An

Alyssa C Ramdyal

Raymond Hsu

Anya Prasitthipayong

The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted, and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term user interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Object identification based on long-term user behavior and short-term interest

The present disclosure generally relates to underwater user interfaces. In some embodiments, a method includes at an electronic device with a display and one or more input devices, receiving a first request to display a user interface for accessing a first function of the electronic device. In response to receiving the first request, and in accordance with a determination that the electronic device is under water, the method includes displaying a first user interface for accessing the first function. In response to receiving the first request, and in accordance with a determination that the electronic device is not under water, the method also includes displaying a second user interface for accessing the first function.

Underwater user interface

The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Growing community of inventors

Sunnyvale, CA, United States of America

Andrew Liu Chen