Microsoft Technology Licensing, LLC

Sharath Viswanathan

Daniel J Hwang

Peter Gregory Davis

Elizabeth Picchietti Salowitz

Juan (Lynn) Dai

Joseph Spencer King

Jose Alberto Rodriguez

Albert Peter Yih

Joseph Bernard Tobens, Iii

Nan Yang

Steven Nabil Bathiche

Scott Randall Shell

Yadhu Nandh Gopalan

Vivek Pradeep

Eric Chris Wolfgang Sommerlade

Loren Kohnfelder

Benjamin M Westbrook

David B Perry

Juan Dai

Upender Sandadi

Andrew D Rogers

Lynn Dai

Neil Laurence Coles

Matthew G Lyons

Angelo Renato Vals

Christopher Ross Jordan

Carlos A C Pessoa

Nathan James Luquetta-fish

Zoheb Vacheri

Zafeiria Anagnostopoulou

Jose Antonio Lara Silva

Machine learning techniques are leveraged to provide personalized assistance on a computing device. In some configurations a timeline of a user's interactions with the computing device is generated. For example, screenshots and audio streams may be saved as entries in the timeline. Context—the state of the computing device when the entry is created, such as which documents and websites are open—is also stored. Entries in the timeline are processed by a model to generate embedding vectors. The timeline may be searched by finding the embedding vector that is closest to an embedding vector derived from a search query. The user may select a query result, causing the associated context to be restored. For example, if the query is 'show me all documents related to my upcoming trip to Japan', the query result may open documents and websites that were open when booking a flight to Japan.

User activity history experiences powered by a machine learning model

In non-limiting examples of the present disclosure, systems, methods and devices for executing gesture operations are provided. A touchpad gesture manager and a touchscreen gesture manager may be maintained. Both managers may comprise the identities of gesture operations and conditions for executing the gesture operations. The conditions for one or more touchscreen gesture operations may be the same as the conditions for one or more corresponding touchpad gesture operations. The gestures that have same conditions for the touchscreen and the touchpad may comprise application window operations and virtual desktop transition operations. In some examples, one or more display elements, animations, or intermediate operations may be different in executing the touchscreen operations than for executing the touchpad operations.

Coherent gestures on touchpads and touchscreens

Techniques are described herein that are capable of causing a control interface to be presented on a touch-enabled device based on a motion or absence thereof. A motion, such as a hover gesture, can be detected and the control interface presented in response to the detection. Alternatively, absence of a motion can be detected and the control interface presented in response to the detection. A hover gesture can occur without a user physically touching a touch screen of a touch-enabled device. Instead, the user's finger or fingers can be positioned at a spaced distance above the touch screen. The touch screen can detect that the user's fingers are proximate to the touch screen, such as through capacitive sensing. Additionally, finger movement can be detected while the fingers are hovering to expand the existing options for gesture input.

Presentation of a control interface on a touch-enabled device based on a motion or absence thereof

Techniques are described herein that are capable of increasing touch and/or hover accuracy on a touch-enabled device. For example, attribute(s) of a hand or a portion thereof (e.g., one or more fingers) may be used to determine a location on a touch screen to which a user intends to point. Such attribute(s) may be derived, measured, etc. For instance, a value corresponding to a distance between the hand/portion and the touch screen may be derived from a magnitude of a measurement of an interaction between the hand/portion and the touch screen. In another example, virtual elements displayed on the touch screen may be mapped to respective areas in a plane that is parallel (e.g., coincident) with the touch screen. In accordance with this example, receiving a touch and/or hover command with regard to an area in the plane may indicate selection of the corresponding virtual element.

Increasing touch and/or hover accuracy on a touch-enabled device

Disclosed herein are representative embodiments of tools and techniques for performing contextual searches using text determined based on digital-ink data. According to one exemplary technique, digital-ink data is received at a computing device and text is determined based on the digital-ink data. Additionally, by an application of the computing device, a contextual search is performed using the text.

Digital ink based contextual search

This disclosure describes techniques of using a centralized rule database to control the abilities of software processes to perform actions with regard to resources provided by a computer. As described herein, each software process executing in a computer executes within a chamber and each resource provided by the computer is associated with a canonical name that uniquely identifies the resource. Furthermore, the computer stores a set of security rules in a centralized rule database. In addition, this disclosure describes techniques of enforcing the rules stored in the centralized rule database.

Centralized enforcement of name-based computer system security rules

Growing community of inventors

Seattle, WA, United States of America

Sharath Viswanathan