Adobe, Inc.

Ronald Eduardo Oribio

Michele Saad

Irgelkha Mejia

Robert W Burke, Jr

Robert Burke

A search system employs arrival times with associated confidence scores as search facets for identifying items. The search system identifies a plurality of items based on search input. An arrival time and associated confidence score are determined for each item from the plurality of items. Search results are provided for the plurality of items in response to the search input. The search results are provided based at least in part on the arrival times and associated confidence scores for the plurality of items.

Delivery-related search and analytics

Systems and methods use machine learning models with content editing tools to prevent or mitigate inadvertent disclosure and dissemination of sensitive data. Entities associated with private information are identified by applying a trained machine learning model to a set of unstructured text data received via an input field of an interface. A privacy score is computed for the text data by identifying connections between the entities, the connections between the entities contributing to the privacy score according to a cumulative privacy risk, the privacy score indicating potential exposure of the private information. The interface is updated to include an indicator distinguishing a target portion of the set of unstructured text data within the input field from other portions of the set of unstructured text data within the input field, wherein a modification to the target portion changes the potential exposure of the private information indicated by the privacy score.

Machine learning modeling for protection against online disclosure of sensitive data

Certain aspects and features of this disclosure relate to chromatic undertone detection. For example, a method involves receiving an image file and producing, using a color warmth classifier, an image warmth profile from the image file. The method further involves applying a surface-image-trained machine-learning model to the image warmth profile to produce an inferred undertone value for the image file. The method further involves comparing, using a recommendation module, and the inferred undertone value, an image color value to a plurality of pre-existing color values corresponding to a database of production images, and causing, in response to the comparing, interactive content including the at least one production image selection from the database of production images to be provided on a recipient device.

Chromatic undertone detection

Systems and methods mitigate aggregate exposure of identifying information using machine learning. A privacy monitoring system identifies entities and corresponding entity types by applying a set of domain-specific neural networks, each trained to recognize a particular entity type, to media data extracted from two or more content items associated with a user. The privacy monitoring system computes a privacy score indicating a cumulative privacy risk for potential exposure of identifying information associated with the user from the two or more content items by identifying connections between the identified entities. The connections between the entities are weighted according to the entity types and contribute to the privacy score. A reporting subsystem outputs an indication of a recommended action for mitigating the cumulative privacy risk.

Machine learning techniques for mitigating aggregate exposure of identifying information

The present technology provides for facilitating removal of undesired search results. In one embodiment, a search request including a search term(s) to use for performing a search is obtained. Thereafter, a search query is generated to execute the search. The search query includes the search terms and a removal parameter indicating a particular search result to exclude from search results returned in response to the search request. A set of search results are provided for display via a user device. Such a set of search results can be identified based on execution of the search query and exclude the particular search result.

Growing community of inventors

Austin, TX, United States of America

Ronald Eduardo Oribio