Abstract: A session shared data system accesses a first communication between a user and a support agent on a first communication channel and stores communication data associated with the first communication in a session shared data object. The session shared data system accesses a subsequent communication between the user and a second agent on a second communication channel, receives a query associated with the subsequent communication and transmits the response to a device of the second agent.

Abstract: A system that enables synchronized interaction between voice input and a visual user interface is described. The system receives, by a network site via a first user interaction channel, a user request to perform an action with a listing network platform. The system establishes, by the network site, a session associated with a session identifier for the user request and provides an option for the user to continue interacting with the listing network platform through a second user interaction channel. The system, in response to receiving input that selects the option, uses the session identifier associated with the session to synchronize a first set of inputs received through the first user interaction channel with a second set of inputs received through the second user interaction channel to complete the action on the listing network platform.

Abstract: A system and method for dynamic cluster personalization is provided. A method of dynamic cluster personalization comprises acquiring information from a user, creating a usage log based on the acquired user information including language information and generating user features based on the usage log. The method further comprises determining a clustering feature from the user features, creating a user cluster based on the clustering feature, determining a personalization feature within the user cluster from the user features, generating a personalization for the user cluster based on the personalization feature and applying the personalization to the users in the user cluster.

Abstract: A method includes extracting a keyword and a slot from a natural language input, where the slot includes information. The method includes determining whether the keyword corresponds to one of a plurality of formation groups. In response to determining that the keyword corresponds to a specific formation group, the method includes updating metadata of the specific formation group with the information of the slot. In response to determining that the keyword does not correspond to any of the formation groups, the method includes determining whether the keyword corresponds to one of a plurality of clusters. In response to determining that the keyword corresponds to a specific cluster, the method includes updating the specific cluster with the information of the slot. In response to determining that the keyword does not correspond to any of the clusters, the method includes creating an additional formation group that includes the keyword and the slot.

Abstract: A method includes extracting a keyword and a slot from a natural language input, where the slot includes information. The method includes determining whether the keyword corresponds to one of a plurality of formation groups. In response to determining that the keyword corresponds to a specific formation group, the method includes updating metadata of the specific formation group with the information of the slot. In response to determining that the keyword does not correspond to any of the formation groups, the method includes determining whether the keyword corresponds to one of a plurality of clusters. In response to determining that the keyword corresponds to a specific cluster, the method includes updating the specific cluster with the information of the slot. In response to determining that the keyword does not correspond to any of the clusters, the method includes creating an additional formation group that includes the keyword and the slot.

Abstract: A system and method for dynamic cluster personalization is provided. A method of dynamic cluster personalization comprises acquiring information from a user, creating a usage log based on the acquired user information including language information and generating user features based on the usage log. The method further comprises determining a clustering feature from the user features, creating a user cluster based on the clustering feature, determining a personalization feature within the user cluster from the user features, generating a personalization for the user cluster based on the personalization feature and applying the personalization to the users in the user cluster.