Abstract: A system and method for providing an adaptive Interaction Logging functionality to help agents reduce the time spent documenting contact center interactions. In a preferred embodiment the system uses a pipeline comprising audio capture of a telephone conversation, automatic speech transcription, text normalization, transcript generation and candidate call log generation based on Real-time and Global Models. The contact center agent edits the candidate call log to create the final call log. The models are updated based on analysis of user feedback in the form of the editing of the candidate call log done by the contact center agents or supervisors. The pipeline yields a candidate call log which the agents can edit in less time than it would take them to generate a call log manually.

Abstract: Techniques for limiting the risk of loss of sensitive data from a mobile device are provided. In one aspect, a method for managing sensitive data on a mobile device is provided. The method includes the following steps. A sensitivity of a data item to be transferred to the mobile device is determined. It is determined whether an aggregate sensitivity of data items already present on the mobile device plus the data item to be transferred exceeds a current threshold sensitivity value for the mobile device. If the aggregate sensitivity exceeds the current threshold sensitivity value, measures are employed to ensure the aggregate sensitivity remains below the current threshold sensitivity value for the mobile device. Otherwise the data item is transferred to the mobile device.

Abstract: A real-time method and system are described for automatically extracting text from the customer-agent interaction at a contact center, analyzing the extracted text to automatically identify one or more customer issues, and performing processing by contact-center agent buddies (CABs) to generate at least one response to the customer issues.

Abstract: Techniques for limiting the risk of loss of sensitive data from a mobile device are provided. In one aspect, a method for managing sensitive data on a mobile device is provided. The method includes the following steps. A sensitivity of a data item to be transferred to the mobile device is determined. It is determined whether an aggregate sensitivity of data items already present on the mobile device plus the data item to be transferred exceeds a current threshold sensitivity value for the mobile device. If the aggregate sensitivity exceeds the current threshold sensitivity value, measures are employed to ensure the aggregate sensitivity remains below the current threshold sensitivity value for the mobile device. Otherwise the data item is transferred to the mobile device.

Abstract: A method for evaluating data includes defining a list of data categories, determining a relative sensitivity to each data category, determining one or more classifiers for each of the data categories, receiving a plurality of data items to be valued, determining one of the data categories for each of said plurality of data items according to the one or more classifiers, and determining a respective sensitivity for each of said plurality of data items.

Abstract: A real-time method and system are described for automatically extracting text from the customer-agent interaction at a contact center, analyzing the extracted text to automatically identify one or more customer issues, and performing processing by contact-center agent buddies (CABs) to generate at least one response to the customer issues.

Abstract: A system and method for providing an adaptive Interaction Logging functionality to help agents reduce the time spent documenting contact center interactions. In a preferred embodiment the system uses a pipeline comprising audio capture of a telephone conversation, automatic speech transcription, text normalization, transcript generation and candidate call log generation based on Real-time and Global Models. The contact center agent edits the candidate call log to create the final call log. The models are updated based on analysis of user feedback in the form of the editing of the candidate call log done by the contact center agents or supervisors. The pipeline yields a candidate call log which the agents can edit in less time than it would take them to generate a call log manually.