The exemplary embodiments disclose a system and method, a computer program product, and a computer system for determining the context of calls and providing a user interface to a user. The exemplary embodiments may include collecting data from the call, extracting one or more features from the collected data, determining a context of the call based on applying one or more models to the extracted one or more features, and providing a user with a user interface.

A computer device may include a memory storing instructions and processor configured to execute the instructions to obtain a text file generated based on a communication session; select topics for classifying communication sessions; and apply one or more trained machine learning models to the obtained text file to determine one or more most likely topics for the communication session. The processor may be further configured to apply regular expression binary classifiers, each associated with a different topic, to the obtained text file to determine a likelihood the communication session is associated with a particular topic; select a topic for the communication session based on the determined one or more most likely topics and the determined likelihood the communication session is associated with the particular topic; and classify the communication session based on the selected topic.

A contextual lead generation in an automated communication link establishment and management system may store information related to sales calls. The system may identify strengths and weaknesses of a sales representative. The system may provide training content to the sales representative in real time base on the identified strengths and weaknesses.

A method starts with processor retrieving member's initial context data. Processor receives a string that is a transcribed utterance or an electronic message from the communication session established between member client device and agent client device. Processor determines potential relationships between the member and a patient that is the subject of the string by processing the string using Long Short-Term Memory (LSTM) neural networks to generate a plurality of relationship values. Relationship values are associated with relationship types. Processor generates weight values based on member's initial context data for each of the plurality of relationship types, and generates probability values for the relationship types based on the relationship values and the weight values. Processor narrows the potential relationships, generates relationship data that includes the narrowed potential relationships, and causes the relationship data to be displayed by the agent client device. Other embodiments are disclosed herein.

The invention provides an interrogator for obtaining information associated with a caller identification, such as a telephone number, transmitted within an incoming telephone call including: a receiving device configured to receive the incoming telephone call and to extract the caller identification from the incoming telephone call; an interrogating device configured to receive the extracted caller identification from the receiving device and to interrogate information associated with the caller identification from an external data base, which is configured to operate independently from the user voice communication device for which the incoming telephone call is intended for; and a forwarding device configured to receive and to forward the interrogated information.

A method for configuring a selected application of a contact center to facilitate handling of incoming interactions. The method may include: collecting data; generating individual customer models and aggregated customer models, wherein the aggregated customer models each comprises an aggregation of a grouping of the individual customer models; generating individual agent models and aggregated agent models, wherein the aggregated agent models each comprises an aggregation of a grouping of the individual agent models; from the customer models, generating a customer predictor configured to predict customer behavior; from the agent models, generating an agent predictor configured to predict agent behavior; using the customer predictor to make a customer prediction; using the agent predictor to make an agent prediction; and modifying an allocation of a contact center resource based on the customer and the agent predictions.

Disclosed are systems and methods for forecasting inbound telecommunications, and more particularly, for analyzing real-time and historical call center data, and applying a forecasting model to said data in order to predict inbound call volume. Additionally, tools are disclosed for manipulating call center data and generating visual representations of metrics pertaining to forecasting call center data via a dashboard.

The exemplary embodiments disclose a system and method, a computer program product, and a computer system for determining the context of calls and providing a user interface to a user. The exemplary embodiments may include collecting data from the call, extracting one or more features from the collected data, determining a context of the call based on applying one or more models to the extracted one or more features, and providing a user with a user interface.

A method starts with processor retrieving member's initial context data. Processor receives a string that is a transcribed utterance or an electronic message from the communication session established between member client device and agent client device. Processor determines potential relationships between the member and a patient that is the subject of the string by processing the string using Long Short-Term Memory (LSTM) neural networks to generate a plurality of relationship values. Relationship values are associated with relationship types. Processor generates weight values based on member's initial context data for each of the plurality of relationship types, and generates probability values for the relationship types based on the relationship values and the weight values. Processor narrows the potential relationships, generates relationship data that includes the narrowed potential relationships, and causes the relationship data to be displayed by the agent client device. Other embodiments are disclosed herein.

Systems, devices and methods are disclosed for controlling and incentivizing the use of software-based services that are made available to residents of controlled-environment facilities. Residents are assigned a communication device that is used to connect to a communication system provided to residents by a controlled-environment facility. Via the assigned communication device, the resident is provided with various software modules, such as visitation software, entertainment software and educational software. The provided software modules may designated as either incentivized or restricted. A restricted module, such as a visitation module or gaming module, is disabled until the resident has been authorized to use the module. The communication device is configured to track the resident's use of incentivized modules, such as education modules. The resident may enable a restricted module for a limited duration by meeting thresholds of use of an incentivized module, such completing milestones provided by the education module.