Salesforce Com, Inc.

Salesforce, Inc.

Sönke Rohde

Brian J Lonsdorf

Owen Winne Schoppe

David J Woodward

Jessica Lundin

Alan Martin Ross

Michael Reynolds Sollami

Didier Prophete

Ronald F Fischer

Mark Francis Movida

Amol Hardikar

Madhav Pathak

Artur Kesel

Jason Schroeder

Akhilesh Gupta

Craig Villamor

Grant Anderson

John Walter Taschek

Charlie Issacs

Steve Gillmor

Scott Bokma

Aashish Jain

Girish Jashnani

Joseph Michael Andolina

Anshu Agarwal

Chetan Ramaiah

Joseph Andolina

Marni Alyse Gasn

Krzysztof Sebastian Oblucki

Markus Spohn

Xing Han

David James Woodward

Disclosed are database systems, computing devices, methods, and computer program products for identifying recurring sequences of user interactions with an application. In some implementations, a server of a database system provides a user interface of the application for display at a computing device. The database system stores data objects identifying a first plurality of user interactions with the application. The server receives information representing a second plurality of user interactions with the application. The server updates the database system to further identify the second user interactions. The server identifies a recurring sequence of user interactions from the first and second user interactions as resulting in a first target state of the application. The server updates the database system to associate the recurring sequence of user interactions with the first target state of the application.

Identifying recurring sequences of user interactions with an application

Techniques are disclosed relating to emphasizing user interface elements for different users based on user attributes. In some embodiments, a system maintains a set of information (e.g., for a particular product) that includes multiple types of information. The system may access the same set of information for different user requests. The computing system may determine first and second subsets of the set of information based on attributes of the different users. The computing system may cause display of a first user interface on a device of the first user showing only the first subset of item fields for the two or more of the first set of items. The computing system may cause display of a second user interface on a device of the second user showing only the second subset of item fields for the two or more of the second set of items.

Adjusting emphasis of user interface elements based on user attributes

Techniques are disclosed for automatically converting a layout image to a text-based representation. In the disclosed techniques, a server computer system receives a layout image that includes a plurality of portions representing a plurality of user interface (UI) elements included in a UI design. The server computer system transforms, via executed of a trained residual neural network (ResNet), the layout image to a text-based representation of the layout image that specifies coordinates of bounding regions of the plurality of UI elements included in the UI design, where the text-based representation is usable to generate program code executable to render the UI design. The disclosed techniques may advantageously automate one or more portions of a UI design process and, as a result save time and computing resources via the execution of an image to text-based conversion ResNet machine learning model.

Automatic image conversion

Systems, devices, and techniques are disclosed for visual text summary generation. An input text may be received. Keywords may be extracted from the input text. Representative keywords may be generated from the keywords. A graph representation of the representative keywords may be generated. Images associated with the representative keywords may be received. A visual-representation style may be selected based on the graph representation of the representative keywords. The images associated with the representative keywords may be arranged according to the selected visual-representation style and the graph representation of the representative keywords.

Visual text summary generation

A method receives an input file. The input file includes a plurality of entries where different entries are associated with a different characteristic. A selection of a guide for an entry is determined where a guide includes guidelines for formatting content in an entry in the plurality of entries. The method performs analyzing an image from the entry to generate image variations. Then, the method analyzes the image and the image variations to place text items from the entry in the image and the image variations where the text items in the image and the image variations are formatted based on the guidelines in the guide for the entry. A plurality of design variants is generated for the entry based on the image and the image variations that include text items.

Region-specific content creation

Embodiments described herein provide a contextual conversation summarization mechanism on a chat platform. Specifically, a communication interface receives a first conversation line originated from a first user and a second conversation line originated from a second user. The mechanism then determines that the first conversational line and the second conversational line belong to a same conversation channel based on a channel indicator. The first conversation line and the second conversation line are concatenated as an input to a summarization model. The summarization model then generates a summary of the conversation channel associated with a timestamp. A first visualization element representing a first conversation contribution by the first user and a second visualization element representing a second conversation contribution by the second user are generated based on the generated summary. A user interface visualization of the summary is generated using the first visualization element and the second visualization element.

Systems and methods for contextual summarization in an online conversation channel

Techniques are disclosed relating to determining a similarity of components of a current webpage to different UI components for use in automatically generating an updated webpage. A computer system may receive information specifying a current webpage, including a particular current UI component and information specifying a plurality of different UI components for an updated webpage. The computer system may identify one or more characteristics of the particular current UI component. The computer system may determine, based on the identified one or more characteristics, a similarity of ones of the plurality of different UI components to the particular current UI component. The computer system may select, based on the determining, a particular different UI component from the plurality of different UI components for use, in the updated webpage, for the particular current UI component. Such techniques may advantageously improve user experience by automatically providing up-to-date user interfaces.

User interface design update automation

Embodiments described herein provide a workflow visualization tracking tool based on text mining on a conversation channel. Specifically, a communication interface receives a plurality of user activity items that are related to a shared work item among the plurality of tenants. A first sequence of status indicators representing a workflow progress of the shared work item over a plurality of time instances may be generated from the plurality of user activity items. A first subset of the plurality of user activity items are determined, which are related to at least one sub-item reflected in the first sequence of status indicators. A second sequence of status indicators representing a second workflow progress of the at least one sub-item over the plurality of time instances may be generated from the first subset of the user activity items. The first sequence of status indicators and the second sequence of status indicators may be presented in a visualization structure via a user interface.

Systems and methods for workflow visualization in a multi-tenant management platform

Techniques are disclosed for automatically generating new content using a trained 1-to-N generative adversarial network (GAN) model. In disclosed techniques, a computer system receives, from a computing device, a request for newly-generated content, where the request includes current content. The computer system automatically generates, using the trained 1-to-N GAN model, N different versions of new content, where a given version of new content is automatically generated based on the current content and one of N different style codes, where the value of N is at least two. After generating the N different versions of new content, the computer system transmits them to the computing device. The disclosed techniques may advantageously automate a content generation process, thereby saving time and computing resources via execution of the 1-to-N GAN machine learning model.

One-to-many automatic content generation

Disclosed herein are system, method, and computer program product embodiments for determining a user-preferred feature type. An embodiment operates by maintaining user-presented features associated with user-presented records, wherein the user-presented features comprise one or more user-presented feature types. After receiving a user-desired feature of the user-presented features, a user-preferred feature type of the user-presented feature types is determined based on the user-presented features and the user-desired feature. Thereafter, a new record and associated feature are to be presented with the new feature being of the user-preferred type.

Learning affinities through design variations

Disclosed herein are system, method and computer readable storage medium for detecting space suitable for overlaying media content onto an image. The system receives a candidate image which may be an image or a video frame. The candidate image is then input into a neural network. The neural network may output coordinates and one or more dimensions representing one or more bounding boxes for inserting media content into the candidate image. The one or more bounding boxes may be transmitted with a request for a media content item to be displayed in a bounding box. In response to the request the media content item may be received, and the candidate image and the media content item overlaid on top of the candidate image within the bounding box may be displayed.

Neural network based detection of image space suitable for overlaying media content

A method for data processing is described. The method includes receiving, from a client of a web service, a request for a web component included in a web page supported by the web service, where the web component is associated with a data structure that defines design characteristics of the web component. The method further includes determining configuration parameters that define stylistic characteristics of the web component based on data attributes of the web page and the data structure associated with the web component, where the configuration parameters are determined using a model trained on a corpus of web pages supported by the web service. The method further includes transmitting, to the client and in response to the request, an indication of the configuration parameters for the web component, where the indication is configured to display the web component according to the stylistic characteristics defined by the configuration parameters.

Techniques for automatically configuring web components

An online system generates a set of content item variations for a reference content item that include different styles of text for the content item. The different styles of text are generated by applying machine-learned style transfer models, for example, neural network based models to reference text of the reference content item. The text variations retain the textual content of the reference text but are synthesized with different styles. The online system can provide the content item variations to users on an online experimental platform to collect user interaction information that may indicate how users respond to different styles of text. The online system or the content providers can effectively target users with content items that include the style of text the users respond to based on the collected information.

Growing community of inventors

San Francisco, CA, United States of America

Sönke Rohde