Microsoft Technology Licensing, LLC

Michael Wilson Daniels

Domenic J Cipollone

Kevin Roland Powell

Zhang Li

Olivier Gauthier

Alice Yingming Lai

William B Dolan

Christopher Brian Quirk

Christopher John Brockett

Ali Taleghani

Theresa Ann Estrada

Kaushik Ramaiah Narayanan

Maria Del Mar Gines Marin

Susan Michele Hendrich

Kylan Matthew Nieh

Kathryn V J Sullivan

Tev'n J Powers

Maria Isabel Carpenter

Juhi Amitkumar Naik

Shikha Devesh Desai

Alfredo R Arnaiz

Siqing Chen

Enrico Cadoni

Davide Turcato

Bhavuk Jain

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

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

A method for providing targeted rewrites can include receiving a selection of text in a file; generating a set of target rewrites of the selection of text, the set of target rewrites comprising: at least one phrase or sentence having semantic similarity to a phrase or sentence of the selection of text; and a style that corresponds to a particular target style, wherein a target style is a representative style for a genre, profession, or environment; and providing for selection one or more of the target rewrites of the set of target rewrites.

Targeted rewrites

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

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Redmond, WA, United States of America

Michael Wilson Daniels