Abstract: Examples described herein provide a digital assistant crafting a response based on target sentiment identification from user input. The digital assistant receives unstructured data input and identifies a segment of the input that includes a facet item. A sentiment associated with the facet item in the segment is identified and classified to identify a targeted sentiment directed towards the facet item. A response is generated based on the targeted sentiment and the facet item.

Abstract: Examples described herein dynamically personalize a digital assistant for a specific user, creating a personal connection between the digital assistant and the user. The digital assistant accesses user activity and generates queries based on the user activity. The digital assistant facilitates natural language conversations as machine learning sessions between the digital assistant and the user using the one or more queries to learn the user's preferences and receives user input from the user during the learning session in response to the queries. The digital assistant dynamically updates a personalized profile for the user based on the user input during the natural language conversations.

Abstract: Described herein is a system for recommending music using a music taste profile. The music taste profile includes information about musical taste of a particular user that can be used to provide music recommendation(s) targeted to that particular user. The system includes a recommendation component that makes a music recommendation(s) based on the music taste profile. The recommendation component can utilize an algorithm to make the music recommendation. With consent of the user, a music taste profile modification component can modify the music taste profile based on an inference from information regarding a music-related interest of the user received from a source (e.g., information obtained about a web browsing search history of the user, signal(s) provided by a digital assistant regarding information requested by the user and/or from a home automation device).

Abstract: Methods and systems are provided for generating personalized greetings for presentation by a personal digital assistant on a client device. An indication is received from the client device associated with the user that the personal digital assistant has been launched on the client device. User-specific information and contextual information is retrieved by querying a user profile database and one or more services. A personalized greeting engine utilizes the user-specific information, such as user inferences and interests, and the contextual information to generate the personalized greetings for presentation by the digital assistant on the client device.

Abstract: Examples described herein dynamically personalize a digital assistant for a specific user, creating a personal connection between the digital assistant and the user. The digital assistant accesses user activity and generates queries based on the user activity. The digital assistant facilitates natural language conversations as machine learning sessions between the digital assistant and the user using the one or more queries to learn the user's preferences and receives user input from the user during the learning session in response to the queries. The digital assistant dynamically updates a personalized profile for the user based on the user input during the natural language conversations.

Abstract: Examples described herein provide a digital assistant crafting a response based on target sentiment identification from user input. The digital assistant receives unstructured data input and identifies a segment of the input that includes a facet item. A sentiment associated with the facet item in the segment is identified and classified to identify a targeted sentiment directed towards the facet item. A response is generated based on the targeted sentiment and the facet item.

Abstract: Methods and systems are provided for generating personalized greetings for presentation by a personal digital assistant on a client device. An indication is received from the client device associated with the user that the personal digital assistant has been launched on the client device. User-specific information and contextual information is retrieved by querying a user profile database and one or more services. A personalized greeting engine utilizes the user-specific information, such as user inferences and interests, and the contextual information to generate the personalized greetings for presentation by the digital assistant on the client device.