Microsoft Technology Licensing, LLC

Matthew Francis Hurst

Mina Mikhail

Riham Hassan Abdel-Moneim Mansour

Saurabh Sanjay Deshpande

Michael Gamon

Danyel Aharon Fisher

Sumit Basu

Arnd Christian König

Dragos A Manolescu

Alexey Maykov

Dmitriy A Belenko

The present disclosure relates to processing operations configured to uniquely utilize indexing of content to improve content retrieval processing, particularly when working with large data sets. The techniques described herein enables efficient content retrieval when working with large data sets such as those that may be associated with a plurality of tenants of a data storage application/service. Among other technical advantages, the present disclosure is applicable to train a classifier using relevant samples based on text search in tenant-specific scenarios, where accurate searching can be executed for content associated with one or more tenant accounts of an application/service concurrently in milliseconds even in instances where there may be millions of documents to be searched. As an example, exemplary data shards may be generated and managed for efficient and scalable content retrieval processing including training of a classifier (e.g., artificial intelligence classifier) and real-time (or near real-time) query processing.

Management of indexed data to improve content retrieval processing

An apparatus to analyze and manipulate biofeedback data is described. The apparatus includes a display that renders a simulated environment. The simulated environment is experienced by a user. The simulated environment is generated by a software program executing on a computer. A biofeedback sensor is coupled to the scalp of the user. The biofeedback sensor measures the electrical activity of the brain of the user when the user experiences the simulated environment. The biofeedback sensor generates electrical signals corresponding to the electrical activity such that the user is able to modify the simulated environment by manipulating the electrical activity in the brain.

Electroencephalograph-based user interface for virtual and augmented reality systems

One or more techniques and/or systems are provided for interactively associating a semantic concept with a unique term that is input by a user. As the user is creating a document and/or once the user has completed a draft of the document, the document is parsed to identify unique terms (e.g., persons, places, things, services, etc.) in the document. When a unique term is identified, a query is generated to locate one or more semantic concepts (e.g., URLs, URNs, or other identifiers, for example) that are associated with the identified unique term and a notification indicative of the results is generated. From this notification, the user can select whether to associate the unique term with any and/or all of the located semantic concepts. In this way, supplemental content may be added to a document that the user is creating, for example.

Interactive addition of semantic concepts to a document

Techniques and systems for assisting an author in creating content for social media (e.g., blog posts, microblogs, tweets, etc.) are disclosed, wherein hints are provided to the author as a function of social media stored in a social media knowledge store. Social media is collected and stored in a social media knowledge store according to some criteria. Upon the happening of some predetermined event, for example, relevant information is retrieved from the social media knowledge store. The relevancy of information may be a function of editing context (provided by the author) and/or social media behavior, for example. The relevant information may be translated into hints that provide an author with suggestions and/or corrections, for example. This information is provided to the author through a social media environment (e.g., an authoring tool) that may be also be capable of receiving input from the author and outputting editing context.

Social media guided authoring

A method and system for retrieving data from a webpage is described herein. A scheduler organizes, or rather orders, a group of webpage identifiers according to some predetermined criteria. Based upon this ordering, a fetcher may be configured to fetch data from webpages identified by the identifiers. To promote efficiency and reduce the latency between when a webpage is updated and when the fetcher retrieves data from the webpage, the scheduler may be configured to reorder the identifiers in such a manner that it causes an identifier that was less relevant, and would not have been sent to the fetcher, to become more relevant. In this way, the method and system may be particularly useful for retrieving data related to webpages that are updated frequently, such as social media webpages, for example.

Method and apparatus for web crawling

An overwhelming number of articles are available everyday via the internet. Unfortunately, it is impossible to peruse more than a handful, and it is difficult to ascertain an article's social context. The techniques disclosed herein address this problem by harnessing implicit and explicit contextual information from social media. By extracting text surrounding a hyperlink to an article in a post and assessing the article as a function of content surrounding the hyperlink, an article's social context is determined and presented. Additionally, articles that are sufficiently similar in content may be grouped to establish a many-to-one relationship between posts and an article, creating a more accurate assessment.

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Seattle, WA, United States of America

Matthew Francis Hurst