Microsoft Technology Licensing, LLC

Jing Han Shiau

John M Sanders

David Gray

Joshua S Bolduc

Bugra Karabey

Roopesh Kumar Rajamani

Kevin H Kahl

Muhammad Ali Siddiqui

Feng Yu

Meenal Srivastva

Subramanian Nagarajan

Patrick S Boyd

Kha Lam

Patrick Steven Boyd

John R Sanders

David Michael Gray

Kevin Holt Kahl

Disclosed herein is a system for minimizing the amount of time it takes to process and understand an unstructured, text-heavy document that includes important security-related information. The system uses a model that implements natural language processing techniques to semantically analyze an unstructured, text-heavy document, in order to identify notable security features useable to resolve the security issues in a more effective and efficient manner (e.g., without the need for a technical security professional). More specifically, the system receives an unstructured document that includes text which may be provided by multiple different security providers. The system is configured to apply the model to various text segments (e.g., a phrase, a sentence, a paragraph, etc.) included in the unstructured document to identify notable security features. The model can then associate the notable security features with a prescribed set of mitigation actions that can be implemented to resolve a security issue.

Automated contextual understanding of unstructured security documents

A remote control service on a mobile device interrogates a program on another computing device to obtain metadata describing the structure of information being displayed on the computing device. The remote control service then calculates a different data structure that is used to display a subset of the data on the display screen of the mobile device.

Remote control for displaying application data on dissimilar screens

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Redmond, WA, United States of America

Jing Han Shiau