Microsoft Technology Licensing, LLC

Carlos A C Pessoa

Steven Nabil Bathiche

Vivek Pradeep

Elizabeth Picchietti Salowitz

Eric Chris Wolfgang Sommerlade

Julien Jacques Ellie

David B Perry

Sharath Viswanathan

James T Jacoby

Nathan James Luquetta-fish

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

The technology provides for rule based data driven validation in which a rule engine identifies which rules are applicable to target data items of a target data object by their data types including any inherited data types. Additionally, a condition for a rule or a rule exemption is implemented also as a rule which is processed by the rule engine like any other rule. In one embodiment, a validation system includes an abstract rule store of rule instance data items which link to corresponding concrete rules which may be in different data formats. A corresponding rule provides access to rule logic which implements the corresponding rule. A rule engine and the abstract rule store may be accessed over a network by an application requesting validation of a target data object. Furthermore, in some examples, the data driven rule store can be implemented using the Microsoft .NET&#x2122; framework.

Rule based data driven validation

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Redmond, WA, United States of America

Carlos A C Pessoa