Abstract: The disclosure is related to mining of text to derive information from the text that is useful for a variety of purposes. The text mining process can be implemented in a service oriented industry such as a call center, where a customer and an agent engage in a dialog, e.g., to discuss product/service related issues. The messages in dialogues between the customers and the agents are tagged with features that describe an aspect of the conversation. The text mining process can mine various dialogues and identify a set of features and messages based on prediction algorithms. The identified set of features and messages can be used to infer an intent of a particular customer for contacting the agent, and to generate a recommendation based on the determined intent.

Abstract: In accordance with an example embodiment a computer-implemented method and an apparatus for predicting and tracking of mood changes in textual conversations are provided. The method includes determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer. Changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation are tracked by the processor. Further, the method includes determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics.

Abstract: In accordance with an example embodiment a computer-implemented method and an apparatus for predicting and tracking of mood changes in textual conversations are provided. The method includes determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer. Changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation are tracked by the processor. Further, the method includes determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics.

Abstract: In accordance with an example embodiment a computer-implemented method and an apparatus for predicting and tracking of mood changes in textual conversations are provided. The method includes determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer. Changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation are tracked by the processor. Further, the method includes determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics.

Abstract: The disclosure is related to mining of text to derive information from the text that is useful for a variety of purposes. The text mining process can be implemented in a service oriented industry such as a call center, where a customer and an agent engage in a dialog, e.g., to discuss product/service related issues. The messages in dialogues between the customers and the agents are tagged with features that describe an aspect of the conversation. The text mining process can mine various dialogues and identify a set of features and messages based on prediction algorithms. The identified set of features and messages can be used to infer an intent of a particular customer for contacting the agent, and to generate a recommendation based on the determined intent.

Abstract: The disclosure is related to mining of text to derive information from the text that is useful for a variety of purposes. The text mining process can be implemented in a service oriented industry such as a call center, where a customer and an agent engage in a dialog, e.g., to discuss product/service related issues. The messages in dialogues between the customers and the agents are tagged with features that describe an aspect of the conversation. The text mining process can mine various dialogues and identify a set of features and messages based on prediction algorithms. The identified set of features and messages can be used to infer an intent of a particular customer for contacting the agent, and to generate a recommendation based on the determined intent.

Abstract: A computer-implemented method and an apparatus for personalizing customer interaction experiences receives an input corresponding to at least one of a business objective and a customer interaction channel. A customer classification framework is selected based on the input. The customer classification framework is associated with a plurality of persona types, where each persona type is associated with a set of behavioral traits. A persona type for a customer is predicted from among the plurality of persona types during an interaction on the customer interaction channel. A propensity of the customer to perform at least one action is predicted based on the persona type. A provisioning of personalized interaction experience to the customer is facilitated based on the predicted propensity of the customer to perform the at least one action.

Abstract: The disclosure is related to mining of text to derive information from the text that is useful for a variety of purposes. The text mining process can be implemented in a service oriented industry such as a call center, where a customer and an agent engage in a dialog, e.g., to discuss product/service related issues. The messages in dialogues between the customers and the agents are tagged with features that describe an aspect of the conversation. The text mining process can mine various dialogues and identify a set of features and messages based on prediction algorithms. The identified set of features and messages can be used to infer an intent of a particular customer for contacting the agent, and to generate a recommendation based on the determined intent.