Project Affinity, Inc.

Autodesk, Inc.

Dropbox, Inc.

Shubham Goel

Hansen Qian

Craig Dabney

Bobby Zhang

Ray Zhou

Gabriel Fan

Patricia Keaney

Anand Rajagopal

Charis Kaskiris

Manu Venugopal

Andrew Luo

Morgan Zerby

Xin Xu

Brad Lee Bitler

Maryam Rezvani

Sigalit Sadeh

Vasanth Krishna Namasivayam

Christopher T Lesniewski-Laas

Arzav Jain

Win Suen

Tristan Inghelbrecht

Sohrab Seyed Fathi

The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine-learning models to classify content items and automatically organize the content items within a file structure according to their content item classifications. For instance, a content item classification system generates one or more content item classification models to determine classifications for content items and/or folders. In some instances, the classification system detects when new content items are added to a smart folder, determines destination folders to which the content items belong based on classifying the content items, and automatically moves the content items accordingly. In various instances, the classification system generates and utilizes a classification model to organize content items into dynamically-generated folders. In example implementations, the classification system generates and utilizes a classification model to automatically organize existing content items into existing folders.

Classifying and organizing digital content items automatically utilizing content item classification models

The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing synthetic visualizations representative of content collections within a content management system. In some cases, the disclosed systems generate a synthetic visualization based on content features that indicate relevance of content items with respect to a user account to emphasize more relevant content items within the synthetic visualization and/or to represent descriptive content attributes of the content items. For example, the disclosed systems can generate a synthetic phrase that represents a content collection and can further generate a synthetic visualization from the synthetic phrase utilizing a synthetic visualization machine learning model.

Synthesizing visualizations for content collections

One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of a method of enhancing online contents based on digital alliance data are disclosed. The method comprising obtaining at least a portion of a webpage at a first user device associated with a first user and a first user account managed by a communication data management server, the webpage listing a plurality of external accounts; and determining that one of the plurality of external accounts corresponds to a contact of an alliance network of the first user. The method further comprises updating the webpage with specific data regarding the contact of the alliance network; and causing displaying the updated webpage by the first user device.

Enhancing online contents based on digital alliance data

One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of a method of enhancing online contents based on digital alliance data are disclosed. The method comprising receiving from a web server a webpage at a first user device associated with a first user and a first user account managed by a communication data management server; extracting a type of data of a plurality types of data from a body or metadata of the webpage; and determining that the type of data matches certain data regarding an organization. The method further comprises updating the webpage with specific data related to one or more members or contacts of an alliance network of the first user account that are associated with the organization; and causing displaying the updated webpage by the first user device.

A computer-implemented method and system provide the ability to determine and provide a safety risk analysis for construction. Construction related data is obtained and includes textual data and a visual artifact for the construction project. A construction safety context is identified based on the construction related data. Based on the construction safety context, a safety participant risk score that assigns a numerical safety risk participant value to any entity involved in the construction project is determined. Based on the safety risk participant score, a safety project score that assigns a risk level on a per-project basis is determined. The safety risk analysis is presented based on the safety participant risk score and safety project score, via a graphical user interface.

Architecture, engineering and construction (AEC) construction safety risk analysis system and method for interactive visualization and capture

A system and method provide the ability to control an architecture, engineering, and construction (AEC) project workflow. AEC data regarding a quality of construction is obtained. A set of classifiers and machine learning models are obtained. The AEC data is augmented based on the set of classifiers and machine learning models. A risk metric is generated for one or more issues in the AEC data based on the augmented AEC data. The risk metric is interactively generated and presented on a display device. Work, project resourcing, and/or training are prioritized based on the risk metric.

Architecture, engineering and construction (AEC) risk analysis system and method

A communication management server computer that manages alliances is programmed or configured to monitor a target strength associated with a user account, which can be an alliance strength of an alliance with an ally of the user account or a relationship strength of a relationship with a contact of the user account. The server is programmed to further take a remedial measure when the monitored target strength deteriorates significantly. The server is programmed to determine the remedial measure based on alliance data, including the set of digital communications shared by the user account or another user account for exploration of relationships. The remedial measure can lead to actions taken by a specific user account that is connected to the user account and the ally or the contact through one or more alliances or relationships.

Managing connection strengths using alliance data

One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of a method of enhancing online contents based on digital alliance data are disclosed. The method comprising receiving from a web server a webpage at a first user device associated with a first user and a first user account managed by a communication data management server; extracting a type of data of a plurality types of data from a body or metadata of the webpage; and determining whether the type of data matches certain data regarding a contact of an alliance network of the first user account. The method further comprises, updating, in response to determining that the type of data matches certain data regarding a contact, the webpage with specific data related to the contact; and causing displaying the updated webpage by the first user device.

A communication management server computer ('server') and related methods are disclosed to create and store digital records representing alliances between user accounts and to use the alliance records in filtering messages or other content and/or determining attributes of messages or content for display. The server allows two electronic devices associated with two user accounts to establish an alliance, where each of the two user accounts offers a set of digital communications for exploration of relationships and agrees to share certain types of information regarding the relationships with the other user account.

Communication-based digital alliance management

A method of managing unanswered digital communications is disclosed. The method comprises identifying, by a processor, a list of digital communications associated with a user account of a user account as expecting a response or a follow-up; determining, by the processor, a group of unanswered digital communications from the list of digital communications; assigning priorities to the group of unanswered digital communications, the priorities indicating an order of responding to the group of unanswered digital communications; transmitting a notification regarding one or more of the group of unanswered digital communications to the user account, the notification including information related to the ranking.

Growing community of inventors

San Francisco, CA, United States of America

Shubham Goel