Microsoft Technology Licensing, LLC

Bernhard Kohlmeier

Madeline Schuster Kleiner

Jon Meling

Jan Heier Johansen

Vegar Skjaerven Wang

Jignesh Shah

Jordi Mola Marti

Jan Anders Nelson

Julie D Bennett

Wei Wu

Mohammed El-Gammal

Torbjørn Helvik

Lori Ann Brownell

Shenghua (Ed) Ye

Pradeep Chilakamarri

Tomasz Lukasz Religa

Vegar Skjærven Wang

Francois Liger

Chenguang Yang

Derik Bjorn Stenerson

Nathaniel George Freier

Robyn Sambo

Amod Anil Agashe

Majd Abbar

Kathryn Richardson

Matthew Crinklaw

Mark Webber

Refaat Issa

Mohamed Elgazzar

Robert L Rounthwaite

Jan-Ove Almli Karlberg

Geoffrey John Hulten

Tor Kreutzer

Michael Gamon

Ariel Fuxman

Patrick Pantel

David Ahs

Cameron B Lerum

Jason Kepner

Ramakrishna Pamarthi

Viraj B Mody

Hongqiao Li

Daniel Fairweather

Vincent Etter

Jan Roelof Falkena

Hao Mi

Seok Woo John Kim

Lin Song

Le Yu

Xiaosong Yang

Riyang Liu

HongQiao Li

Byung Kun Lee

Pankaj Gaur

An in-application search service receives a query from a user attempting to locate information within a document. If a current index and current vector table do not exist, a content indexing service produces an index and a vector table based on the current content of the document. The vector table is based on semantic models that have been pre-trained. The query is tokenized and one of three different processing paths are taken based on the length of the tokenized query. For a single term query, a semantic search and prefix search are performed and the results are combined. If the length of tokenized query exceeds a threshold, a semantic search produces the results. Otherwise, search results are produced based on both prefix fanout and semantic fanout. Results are deduplicated, snippets are extracted, and the results and/or snippets are presented to the user.

Smart find for in-application searching

A method and system for intelligently organizing one or more groups of relevant files may include retrieving a user data signal including user-specific data, analyzing the user data signal to identify a parameter relating to file relevance, identifying one or more relevant files in a storage medium based on the parameter at least one of a user category property, a lifecycle stage property, a relevant activity property, or an activity level property of one or more files in the storage medium, organizing the one or more relevant file into the one or more groups of relevant files, and providing for display data relating to the one or more groups of relevant files.

Intelligently identifying and grouping relevant files and providing an event representation for files

A method and system for receiving data relating to one or more activities performed by a user on a document within a specific time period, the one or more activities being performed by using an application, analyzing the data to identify a category of user activity based at least on the type of activity performed on the document, and transmitting a signal to a device for storage in association with the document, the signal including the identified category.

Intelligently identifying a user's relationship with a document

Described herein are mechanisms to allow users to access functionality of applications in a suite of applications. In a first aspect, when a query relating to functionality of an application is received from a user, an index containing both top-level and sub-level functionality is searched. Results are ranked using a trained machine learning model using both context describing user interactions and the search results. A subset of the ranked results are presented to the user as options. In a second aspect the index can comprise entries describing functionality from other applications so that results presented to the user can include cross-application functionality. In a third aspect, the index can be searched using the context prior to receiving a query and adjusting the user interface based on the results. In a fourth aspect, the system can recommend other applications and/or devices that are better suited to a user's intent.

Deep command search within and across applications

A method and system for providing one or more suggested application features to a user of an application may include receiving an indication of a user action in a document, accessing contextual document data associated with the document, providing at least one of information about the user action or the contextual document data as input to a machine-learning (ML) model to predict a desired intent for the document, obtaining the predicted desired intent as an output from the ML model, identifying based on the predicted desired intent one or more application features that fulfil the desired intent, and providing data about the one or more application features for display.

Intelligent feature identification and presentation

A method and system for intelligently ranking search results may include receiving a search request containing one or more terms for performing a search, providing the one or more terms for conducting a search, and receiving a search results index containing a list of a plurality of documents, each of the plurality of documents corresponding to one of the one or more terms or to one or more other terms associated with the at least one of the one or more terms. Once the search results index is received, the method and system may access a plurality of properties associated with at least one of the plurality of documents, the plurality of properties including a user category associated with the at least one of the plurality of documents, calculating a relevance score for the at least one of the plurality of documents based on at least one of the plurality of properties, selecting a subset of the plurality of documents for presenting to a user based at least on the calculated relevance score, and providing the subset of plurality of documents for presenting to the user.

Intelligent ranking of search results

Examples of the present disclosure describe systems and methods for determining authoritative documents based on implicit interlinking and communication signals. In aspects, a search operation may be initiated from one or more applications or services. The search operation may be processed to identify search information, such as one or more content items, content topics, or entities. The identified search information may be used to search one or more data sources for implicit relationships between the search information and content items and/or entities stored by the data sources. The results of the search may be collected and ranked according to one or more criteria. The ranked results may be provided in response to the search operation.

Determining authoritative documents based on implicit interlinking and communication signals

A method and system for intelligently notifying collaborators of activity on collaborative content include receiving a first indication of a first collaboration activity performed on a first document by a first collaborator among a plurality of first collaborators associated with the first document and responsive to receiving the first indication, obtaining first activity information for the first document comprising the first collaborative activity and one or more second collaborative activities performed on the first document. The method and system determine a lifecycle stage of the first document, analyze the first activity information and the lifecycle stage of the first document to identify one or more second collaborators among the plurality of first collaborators associated with the first document to notify of the first collaborative activity, and provide for displaying the first collaboration activity to the one or more second collaborators.

Notifications regarding updates to collaborative content

A method and system for identifying potential collaborators for a document may include determining a lifecycle stage of a document, determining a subject matter of the document based at least in part on content of the document. The method and system identify one or more potential collaborators to contribute to the document based at least in part on the subject matter of the document, a lifecycle stage of the document, or collaborator-specific information associated with each of the one or more potential collaborators. The method and system may also include providing data relating to the one or more potential collaborators for display.

Intelligently identifying collaborators for a document

A method and system for providing a personalized user interface and personalized search suggestions when using an application is disclosed. The method includes receiving a request for providing a personalized user interface such as a personalized menu for an application and examining a history of the user's usage of the application, a history of other user's usage of the application, and/or the content of the current document in the application, before identifying one or more suggested options offered by the application based on one or more of these factors. A list may then be generated and provided for being displayed as part of the personalized user interface. Upon receiving an indication of a user's intent to perform a search within the application, the user's usage history, usage history of users with similar activities, and/or content of the current document may be examined to provide the user with a list of search suggestions.

Personalized user experience and search-based recommendations

A document lens service identifies an end-user targeted to consume a productivity document being authored in a user interface to a productivity application. The service then also identifies a document profile specific to the end-user indicative of a model document for the end-user to consume. While the productivity document is being authored, suggestions may be surfaced in the user interface for aligning the productivity document with the model document.

Enhanced document services

Growing community of inventors

Seattle, WA, United States of America

Bernhard Kohlmeier