Abstract: Embodiments described herein include aspects related to generating a layout-aware background image. Aspects of the method include receiving a training dataset comprising a document. The method further includes obtaining a mask image based on a layout of content in the document, the mask image having a content area corresponding to content of the document. The method further includes training a machine learning model using the mask image to provide a trained machine learning model that generates transparency values for pixels of a background image for the document.

Abstract: Embodiments described herein are directed to enabling a user to modify data stored locally during a data migration process in which the user's data is being transferred to the cloud. For instance, a synchronization service requests the user's device (e.g., a client-based server) to provide a hash value for each data object maintained thereby (including modified data objects) and compares the hash values to hash values generated for the data uploaded to the cloud. If a hash value provided by the server does not match any of the hash values generated for the uploaded data, this means that the data object associated with the unmatched hash value has been modified since the initiation of the data transfer process. The synchronization service receives the modified data object from the server and uploads it to the cloud, thereby synchronizing the data uploaded to the cloud with the data locally-maintained by the server.

Abstract: Embodiments described herein are directed to enabling a user to modify data stored locally during a data migration process in which the user's data is being transferred to the cloud. For instance, a synchronization service requests the user's device (e.g., a client-based server) to provide a hash value for each data object maintained thereby (including modified data objects) and compares the hash values to hash values generated for the data uploaded to the cloud. If a hash value provided by the server does not match any of the hash values generated for the uploaded data, this means that the data object associated with the unmatched hash value has been modified since the initiation of the data transfer process. The synchronization service receives the modified data object from the server and uploads it to the cloud, thereby synchronizing the data uploaded to the cloud with the data locally-maintained by the server.

Abstract: This document describes techniques of user-based content filtering. The techniques receive content of a selected category from one or more sources, filter the content received from the one or more sources based on predefined settings for the user, and present at least some of the filtered content in a portion of a single user interface. By so doing, users can quickly and easily access filtered content via the single user interface.

Abstract: Compliance-relevant data from external systems comprising managed entities can be received, stored, processed, transformed and evaluated in an automated fashion. Compliance reporting can be generated dynamically to reflect the most current regulations, guidance and system operating conditions. Compliance data from external systems can be converted into a unified format compatible with a compliance management schema. A series of transformations can be applied to the compliance-relevant data. A compliance threshold can be provided to the compliance management system and compliance scoring can be provided.