Abstract:
Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving unstructured natural language information from at least one user. The method also includes, in response to receiving the unstructured natural language information, determining whether event information is present in the unstructured natural language information. The method further includes, in accordance with a determination that event information is present within the unstructured natural language information, determining whether an agreement on an event is present in the unstructured natural language information. The method further includes, in accordance with a determination that an agreement on an event is present, determining an event type of the event and providing an event description based on the event type.
Abstract:
The present disclosure generally relates to user interfaces for navigating, viewing, and editing content items, including aggregated content items.
Abstract:
Embodiments of the present disclosure present devices, methods, and computer readable medium for presenting a user interface that allows a user to quickly and easily filter and search a digital asset collection. The disclosed techniques allow for rapid recall of desired digital assets, linking assets into logical collections, and an overall improved user experience. The zero keyword/contextual keyword feature presents multimedia content icons and searchable keywords to allow a user to search the digital asset collection simply by tapping on one of these keywords. The top auto completion feature auto-completes suggestions in the search field based on various heuristics to ensure the method produces diverse and relevant results. The next keyword suggestion feature predicts a next search term based on learned properties about the digital asset collection.
Abstract:
Techniques of digital asset management (DAM) are described. A DAM system can obtain a knowledge graph metadata network describing relationships between metadata associated with a user's collection of digital assets (DAs), e.g., images, videos, music, etc. Based on information obtained, e.g., from the user's DA collection and/or the knowledge graph metadata network, the DAM system may provide users with more intelligent (and automated) DA sharing suggestions that are as relevant as possible for a given context. In some embodiments, the sharing suggestions may be based on one or more DAs recently shared with the user from a third party. In other embodiments, a proactive sharing suggestion may be presented to a user based on a detected indication of an intent to share DAs, e.g., based on the extraction of relevant features from an incoming message from a third party (or an outgoing message from the user to a third party).
Abstract:
Techniques for digital asset classification are described. One or more holiday score are assigned to a set of digital media assets. The one or more holiday scores are calculated based on weighted holiday metrics determined based on characteristics of the set of digital assets. A holiday classification is assigned based on the one or more holiday score, and the set of digital media assets are provided for presentation in accordance with the holiday classification.