Microsoft Technology Licensing, LLC

Domenic J Cipollone

Kevin Roland Powell

Michael Wilson Daniels

Ali Taleghani

Ravi Chandru Shahani

Michael V Calcagno

Su Chin Chang

David Parkinson

Mari J B Olsen

Maria Del Mar Gines Marin

Kathryn V J Sullivan

Theresa Ann Estrada

Kylan Matthew Nieh

Alfredo R Arnaiz

Tev'n J Powers

Shikha Devesh Desai

Kaushik Ramaiah Narayanan

Zhang Li

Susan Michele Hendrich

Olivier Gauthier

Alice Yingming Lai

Leah Joy Brown

Robert Andrew Little

William B Dolan

Christopher Brian Quirk

Christopher John Brockett

Kyle Matthew Von Haden

Siqing Chen

Enrico Cadoni

Maria Isabel Carpenter

Davide Turcato

Juhi Amitkumar Naik

Bhavuk Jain

Amy Tremper

Paul Rustam Karimov

Kevin Field

Kevin Michael Black

Laura Licari

Marion Kremer

Sean Aubrey Oldridge

An editor service receives a textual input. The editor service provides the textual input to a rule-based grammar checker to obtain a grammar checker result. The editor service also provides the textual input to a machine learning (ML) fluency model that checks the textual input for errors and provides a ML model result. The editor service aggregates the grammar checker result and the ML model result and generates an editor service output based upon the aggregated results. A representation of the editor service result is provided to the client computing system for surfacing through a user interface.

Using editor service to control orchestration of grammar checker and machine learned mechanism

The present disclosure relates to processing operations configured to provide a linguistic-based approach to evaluating repetition in content of an electronic document. The approach of the present disclosure is about detecting terms/words/phrases that are likely to be perceived as being repetitious by native speakers of a language rather than just identifying the occurrence of identical words or strings in a document as done by traditional language checks. Processing of the present disclosure detects and evaluates terms or phrases using positive linguistic evidence derived from evaluation of linguistic relationships between words in a string in syntactic ways. This results in more accurate and efficient determination as to whether a term is truly repetitious at the linguistic level as compared with traditional language checks. As compared with string-based evaluation, fewer flags are raised for identification of repetitive/over-used language, but more precise/accurate identification of repetition occurs using processing of the present disclosure.

Systems and methods for identification of repetitive language in document using linguistic analysis and correction thereof

Status-based reading and authoring assistance is provided. A status-based reading and authoring assistance feature can automatically determine a status of a user and automatically adapt reading and authoring tools provided for display based on the determined status. The status-based reading and authoring assistance feature provides the right reading and authoring tools at the right time, according to the current use of the application. During a user session with respect to a productivity application that includes status-based reading and authoring assistance, signals (e.g., user actions and context information) associated with a file can be received. A status regarding the use of the file can be determined using at least the signals. The status can comprise a reading status or an authoring status (or even a sub status). Reading and authoring tools provided for a display of the productivity application can be adapted based on the status during the user session.

Status-based reading and authoring assistance

A method and system for providing replacement text segments for a given text segment may include receiving a request to provide the replacement text segment for the text segment in the document, examining a content characteristic of the document, and examining at least one of user-specific information, organization-specific information, or non-linguistic features of the document, before identifying at least one replacement text segment for the text segment, via a machine translation system, based on the content characteristic of the document and at least one of the user-specific information, the organization-specific information, or the non-linguistic features of the document. The method and system may include providing the identified replacement text segment for display to a user, receiving an input indicating a user's selection of the identified replacement text segment, and upon receiving the input, replacing the text segment in the document with the identified replacement text segment.

Method and system for intelligently suggesting paraphrases

Systems and methods may be used to display document critiques on a display device. A method may include receiving information including a document type of a document. The method may include determining a set of critiques for use with the document type, the set of critiques including a critique specific to the document type. The method may include providing, on a display, feedback within the document, including a visual indication on a user interface presenting the document, based on the set of critiques, for text within the document.

Automatic document assistance based on document type

A system and method includes dividing content of an electronic document into components. A document type of the electronic document is identified by comparing a document score against a document type criterion, the document score being based on a combination of a component score of each of the components. A user interface provides an indication of the document type.

Electronic document content augmentation

A system and method includes receiving content of an electronic document having a document type, the content divided into components each having a unique identifier and selecting an extraction schema based on the document type, the extraction schema having a plurality of data categories. For each of the components, the extraction schema is applied to identify content of the component that corresponds to individual ones of the data categories and saving, with the processor, in an electronic data storage, in a record associated with the component, category metadata indicative of content of the component corresponding to the data categories. In response to obtaining the category metadata for each of the components, applying the extraction schema to the content metadata of each of the components and to the electronic document as a whole to determine document metadata. A user interface displays the document metadata on the user interface.

Electronic document content extraction and document type determination

A system and method includes receiving an electronic document having content divided into components and, for each of the components, comparing content of the component with component content characteristics of a classification schema associated with a document type and storing, in an electronic data storage, in a record associated with the component, indications of the component content characteristics of the classification schema that are included in the component. Document content characteristics of the classification schema are compared with the content of the electronic document and storing, in the electronic data storage, in a record for the electronic document, indications of the document content characteristics of the classification schema that are included in the electronic document. The electronic document is identified as the document type based on the content characteristics of the records meeting a document type criteria.

Electronic document content classification and document type determination

Techniques for automatic proofing of textual data is described. In one embodiment, these techniques are directed towards producing proofed textual data for various operational environments via logic operative on a logic circuit to access information comprising a set of n-grams, at least one mapping between at least one replacement n-gram and a corresponding n-gram in the set of n-grams, and a corresponding confidence score for each mapping being determined by user activity while producing text for various applications; process input to a productivity application comprising textual data and identify a portion thereof to replace based upon the accessed information; and automatically modify the portion of the textual data using a replacement n-gram selected from the replacement n-grams based upon a corresponding confidence score between the portion of the textual data and the replacement n-gram. Other embodiments are described and claimed.

Techniques for automatic proofing of textual data

A system and method includes obtaining content extracted from an electronic document, the electronic document having a document type. At least some of the content is transmitted to an online social networking system based on the document type. A recommended content change is received from the online social networking system. A user interface dynamically displays the recommended content change concurrently with display of the electronic document as the electronic document is updated.

A framework for generating a semantic interpretation of natural language input includes an interpreter, a first set of types, and a second set of types. The interpreter is adapted to mediate between a client application and one or more analysis engines to produce interpretations of the natural language input that are valid for the client application. The first set of types is adapted to define interactions between the interpreter and the one or more analysis engines. The second set of types is adapted to define interactions between the interpreter and the client application.

Semantic framework for natural language programming

A software development tool for programming natural language software applications is described. The software development tool includes a programming language and a compiler. The programming language has a set of programming constructs for facilitating natural language programming. The compiler is adapted to take a software program containing instances of the set of programming constructs and to generate a software application.

Semantic programming language

A lexical semantic structure for modeling semantics of a natural language input on a computer is described. A set of lexical semantic categories is selected to model content of the natural language input. A methodology associates content of the natural language input to one or more categories of the set of lexical semantic categories.

Lexical semantic structure

A system for developing natural language enabled software applications is described. Resolvable types define abstract representations of linguistic elements and interrelationships between linguistic elements of a natural language input. Resolution semantics define procedural rules for resolving validity of the resolvable types in a natural language enabled software application.

Resolvable semantic type and resolvable semantic type resolution

A linguistic object model is adapted to model semantic elements of a natural language. The linguistic object model includes a set of abstract representations of semantic elements of an utterance. Each abstract representation in the set corresponds to a natural language type that is independent of any particular language.

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Redmond, WA, United States of America

Domenic J Cipollone