Abstract: Techniques to response to respond to user requests using natural-language machine learning based on branching example conversations are described.

Abstract: Techniques to predictively respond to user requests using natural language processing are described. In one embodiment, an apparatus may comprise a client communication component operative to receive a user service request from a user client; an interaction processing component operative to submit the user service request to a memory-based natural language processing component; generate a series of user interaction exchanges with the user client based on output from the memory-based natural language processing component, wherein the series of user interaction exchanges are represented in a memory component of the memory-based natural language processing component; and receive one or more operator instructions for the performance of the user service request from the memory-based natural language processing component; and a user interface component operative to display the one or more operator instructions in an operator console. Other embodiments are described and claimed.

Abstract: In one embodiment, a method includes scoring a set of content objects based on one or more user-engagement factors, identifying one or more related content objects, wherein each related content objects is connected within the online social network to one or more content objects of the set of content objects having a score greater than a threshold score, generating a plurality of structured queries that each comprise references to one or more content objects, wherein at least one of the structured queries is a personalized query comprising a reference to at least one of the related content objects, and sending instructions to a client device for presenting one or more of the generated structured queries to a first user for display on an interface currently accessed by the first user, wherein at least one of the sent structured queries is a personalized query.

Abstract: Techniques to predictively respond to user requests using natural language processing are described. In one embodiment, an apparatus may comprise a client communication component operative to receive a user service request from a user client; an interaction processing component operative to submit the user service request to a memory-based natural language processing component; generate a series of user interaction exchanges with the user client based on output from the memory-based natural language processing component, wherein the series of user interaction exchanges are represented in a memory component of the memory-based natural language processing component; and receive one or more operator instructions for the performance of the user service request from the memory-based natural language processing component; and a user interface component operative to display the one or more operator instructions in an operator console. Other embodiments are described and claimed.

Abstract: Techniques to response to respond to user requests using natural-language machine learning based on branching example conversations are described.

Abstract: Techniques to predictively respond to user requests using natural language processing are described. In one embodiment, an apparatus may comprise a client communication component operative to receive a user service request from a user client; an interaction processing component operative to submit the user service request to a memory-based natural language processing component; generate a series of user interaction exchanges with the user client based on output from the memory-based natural language processing component, wherein the series of user interaction exchanges are represented in a memory component of the memory-based natural language processing component; and receive one or more operator instructions for the performance of the user service request from the memory-based natural language processing component; and a user interface component operative to display the one or more operator instructions in an operator console. Other embodiments are described and claimed.

Abstract: In one embodiment, a method includes scoring a set of content objects based on one or more user-engagement factors, identifying one or more related content objects, wherein each related content objects is connected within the online social network to one or more content objects of the set of content objects having a score greater than a threshold score, generating a plurality of structured queries that each comprise references to one or more content objects, wherein at least one of the structured queries is a personalized query comprising a reference to at least one of the related content objects, and sending instructions to a client device for presenting one or more of the generated structured queries to a first user for display on an interface currently accessed by the first user, wherein at least one of the sent structured queries is a personalized query.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges. A first node corresponds to a first user associated with an online social network and second nodes correspond to a concept or a second user. The method further comprises scoring a first set of nodes of the second nodes based on user-engagement factors. The method further comprises identifying common nodes that are connected by edges to nodes of the first set of nodes that have a score greater than a threshold score. The method further comprises generating structured queries and sending the structured queries to the user, the sent structured queries being a personalized query.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges. A first node corresponds to a first user associated with an online social network and second nodes correspond to a concept or a second user. The method further comprises scoring a first set of nodes of the second nodes based on user-engagement factors. The method further comprises identifying common nodes that are connected by edges to nodes of the first set of nodes that have a score greater than a threshold score. The method further comprises generating structured queries and sending the structured queries to the user, the sent structured queries being a personalized query.