Abstract: A text-based real-time communication interface, such as a chatbot, is presented to a user for the exchange of customer support information. A user's freeform text input is analyzed using machine learning algorithms to derive the meaning of the input text as well as to determine the user sentiment expressed therein. These determinations may be further supported by signals extracted from session-based activity, which signals can be used to infer the intended workflow of the user and whether or not that workflow was achieved. The expressed user sentiment is considered along with other historical or session-based user data to generate tailored questions and responses to be delivered in real-time to the user. The responses are displayed to the user along with information that routes the user to a workflow resolution.

Abstract: A text-based real-time communication interface, such as a chatbot, is presented to a user for the exchange of customer support information. A user's freeform text input is analyzed using machine learning algorithms to derive the meaning of the input text as well as to determine the user sentiment expressed therein. These determinations may be further supported by signals extracted from session-based activity, which signals can be used to infer the intended workflow of the user and whether or not that workflow was achieved. The expressed user sentiment is considered along with other historical or session-based user data to generate tailored questions and responses to be delivered in real-time to the user. The responses are displayed to the user along with information that routes the user to a workflow resolution.

Abstract: A server receives a request for a service from a first user that defines a location for the service and a category of the service. A first stage of matching is performed that includes determining second users that match the location and category. A second stage of matching is performed that includes performing for each second user: computing a first value that quantifies an attractiveness of the request to that second user, computing a second value that quantifies a likelihood of the first user selecting that second user to fulfill the request, and computing a third value based at least in part on the computed first and second values. A request for the service is transmitted to at least some of the second users whose computed third value exceeds a first threshold value.