Abstract: A computer-implemented method for automating actions for a customer in relation to an interaction between the customer and an agent of a contact center, the interaction including an exchange of statements made by the customer and agent. The method includes the steps of: receiving a transcript of the interaction; via a first analysis, analyzing the transcript; from results of the first analysis, identifying: a pending action, wherein the pending action is an action promised by the customer or agent that will be resolved after the interaction; and a target timeframe for resolving the pending action; given the pending action, determining a follow-up workflow that includes one or more follow-up actions, each of the one or more follow-up actions comprising an action intended to assist the customer to resolve the pending action; and automatically executing the one or more follow-up actions.

Abstract: 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.

Abstract: A method for implementing an enterprise's outbound campaign in which an offer is communicated to target customers in a manner personalized for each. The method includes: providing a customer profile database; providing a personalization platform; updating the customer profile of a first target customer according to data received from a personal bot running on a device of the first target customer; deriving interaction predictors for the first target customer relating to behavioral tendency for a interaction type; receiving an enterprise campaign dataset from the enterprise related to the outbound campaign, the enterprise campaign dataset including: information describing the offer, context; and list of the target customers; augmenting, at the personalization platform, the enterprise campaign dataset with the interaction predictors related to the first target customer to produce an enriched campaign dataset; and transmitting the enriched campaign dataset to the enterprise.

Abstract: A method for personalizing a delivery of services to a first customer including: providing a customer profile; updating the customer profile via performing a first process to collect interaction data, the first process including the steps of: monitoring activity on the communication device and, therefrom, detecting the first interaction with the first contact center; identifying data relating to the first interaction for collecting as the interaction data; and updating the customer profile to include the interaction data identified from the first interaction; generating an interaction predictor, the interaction predictor comprising knowledge about the first customer derived, at least in part, from the data stored within the customer profile, the knowledge comprising a behavioral factor attributable to the first customer given a first type of interaction; and augmenting the customer profile by storing therein the interaction predictor.

Abstract: A processor receives inputs from a dialog between an agent and a user performed over a communication channel A knowledge base is stored, comprising entries with a subset of said entries defined as higher priority. A match is detected between an input from said dialog and a plurality of said knowledge base entries. At least one of said plurality of entries is retrieved corresponding to said match. The at least one of said plurality of entries is pushed as an output to one or more of a device operated by said user and at least one device operated by one of said user and said agent. A further match is detected between an input from said dialog and a higher priority entry in said knowledge base and pushed to said at least one device while the dialog is ongoing.

Abstract: A method is presented for executing a dialog turn in a conversation by a dialog manager comprising: receiving an input associated with a task from a user; passing the input to an NLU engine on a first task path; receiving a list of possible intents associated with the task, wherein the list of possible intents comprises an associated confidence for each of the possible intents; applying context-aware re-scoring of the confidences from the NLU engine with weight applied to one or more tasks currently active with the user; selecting an intent based on the re-scored confidences; determining a new task path in a hierarchy of intents based on the confirmed intent; confirming the selected intent and associated slots; and selecting a response flow for the new task path in the hierarchy of intents and executing the response flow.

Abstract: A root behavior tree is stored with a flow control node and a plurality of child nodes. The flow control node may determine a sequence of execution of child nodes. A first-level behavior tree is stored and executed to accomplish a task with associated intent. The first-level tree comprises a child node of the root tree and nodes defining actions. A dialog between contact center and user is hosted over a communication channel and a processor receives inputs from the dialog and executes the root tree and the first-level tree as a child node of the root tree in response. Upon detecting a match between an input and a data pattern, the execution sequence within the root tree or a further tree is altered. Responsive to the altered sequence, an output is provided to cause an action.

Abstract: A computer-implemented method for managing a dialog between a contact center system and a user thereof, comprising the steps of: hosting a dialog over a communication channel between an automated dialog engine of said contact center and said user thereof, said dialog comprising messages sent between said automated dialog engine and said user in both directions; said automated dialog engine receiving input messages from said user, and determining response messages in response to said inputs; detecting from said messages of said dialog a trigger event matching a rule; in response to detection of said trigger event: providing said agent station with a summary of said dialog; and providing control of said automated dialog engine to said agent station.

Abstract: A method for protecting personal data pursuant to behavioral factors unique to a first customer. The method includes: storing a customer profile of the first customer that includes transaction data from transactions with entities; providing a personal assistant that is configured to access the customer profile pursuant to engagement rules to conduct the transactions; updating the customer profile pursuant to a first new transaction; generating a predictor from the updated customer profile, the predictor including knowledge about the first customer derived from the updated customer profile including a behavioral factors attributable to the first customer given a characteristic related to the first new transaction; augmenting the customer profile by storing therein the predictor, wherein the predictor: modifies at least one of the rules of the engagement rules and links the behavioral factor to the characteristic of the first transaction.

Abstract: A system and method are presented for generating staffing requirements for deferred work in a contact center environment. In an embodiment, a simulation of deferred work performance is used to generate staffing requirement. Information, such as volume offered, expected handle time, available staff distributed throughout the intervals over a period of time, etc., are utilized for determining service performance metrics. The simulation accounts for transient data (e.g., number of deferred work handled or completed, number of backlog from an interval to the next, starting number of deferred work in the system, etc.) and determines performance metrics using that transient data.

Abstract: Methods, systems, and computer program product for automatically performing sentiment analysis on texts, such as telephone call transcripts and electronic written communications. Disclosed techniques include, inter alia, lexicon training, handling of negations and shifters, pruning of lexicons, confidence calculation for token orientation, supervised customization, lexicon mixing, and adaptive segmentation.

Abstract: Methods, systems, and computer program product for automatically performing sentiment analysis on texts, such as telephone call transcripts and electronic written communications. Disclosed techniques include, inter alia, lexicon training, handling of negations and shifters, pruning of lexicons, confidence calculation for token orientation, supervised customization, lexicon mixing, and adaptive segmentation.

Abstract: Methods, systems, and computer program product for automatically performing sentiment analysis on texts, such as telephone call transcripts and electronic written communications. Disclosed techniques include, inter alia, lexicon training, handling of negations and shifters, pruning of lexicons, confidence calculation for token orientation, supervised customization, lexicon mixing, and adaptive segmentation.

Abstract: A system and method are presented for the addition of content to contact center interactions. An interaction is routed to an agent in the contact center environment. The interaction is routed through one or more providers of embedded client applications. Providers may be a first party, a DSL provider, or a programmatic provider. The provider triggers a user interface which displays one or more specified embedded client applications to the agent and when the agent selects one of the applications, it is asynchronously loaded through an inline frame.

Abstract: A method for managing automated resources that includes: calculating a channel RIQ score for a first bot in relation to a first communication channel and using it to modify a deployment of the first bot. The calculating the channel RIQ score for the first bot may include: identifying a first engagement scenario that the first bot is able to perform via the first communication channel; identifying target bot capabilities for performing the tasks of the first engagement scenario via the first communication channel; collecting performance data related to the first bot performing the first engagement scenario via the first communication channel; calculating the channel RIQ score by comparing: the performance data related to the first bot performing the first engagement scenario; and the target bot capabilities for performing the first engagement scenario via the first communication channel.

Abstract: A system and method are presented for delivering modular tools through a cloud-based remote computing environment. Users may create and customize extensions to the modular tools for integration with the product system without requiring change to product. Using a script tag added to a website, a user is able to install the modular tool to a website. The modular tool extensions are able to directly communicate with handlers and websites and are able to become directly integrated with a premises-based product. This may be done through a multiplexed API exposed to the modular tool extensions that directly couples them to the premises-based product. The modular tools are able to be configured in the premises-based product, however they are hosted in the cloud and as such, the premises-based product is able to receive continuous integration and deployment from the cloud.

Abstract: A system and method are presented for the correction of packet loss in audio in automatic speech recognition (ASR) systems. Packet loss correction, as presented herein, occurs at the recognition stage without modifying any of the acoustic models generated during training. The behavior of the ASR engine in the absence of packet loss is thus not altered. To accomplish this, the actual input signal may be rectified, the recognition scores may be normalized to account for signal errors, and a best-estimate method using information from previous frames and acoustic models may be used to replace the noisy signal.

Abstract: A system is presented for load balancing across media server instances. In an embodiment, media is broken out into a multi-tenanted service allowing the media to be scaled independently of the number of organizations supported on a cloud-based collaboration platform. Scaling may occur in a scaling-out or a scaling-in operation. States for a media service may comprise in-service, quiescing, quiesced, failed, etc. The states may be used to monitor sessions associated with an instance and determine which media instances to terminate during a scaling-in operation. In an embodiment, new instances may be added to a collection of media instances in response to an increased workload in a scaling-out operation.

Abstract: A system and method are presented for invoking integration actions in a unified collaboration system. A client communicates with a bridging web server through a ReST. The bridging web server comprises a cloud service which facilitates communication with integration servers, which may be located on-premises. In an embodiment, the integration server(s) host a number of plugins which are capable of implementing integration actions. The bridging web server decides which action implementation is the best one to service a request. The implementation may be based on prior configuration. Routing decisions on the bridging web server may be automatically selected based on prior configuration.

Abstract: A method for routing interactions arriving at a contact center. The method may include: providing a cost schedule for the interactions that includes a classifier in which categories of interaction types are defined and a cost value corresponding to each of the interaction types; providing a capacity value for agents; and routing the interactions in accordance with a routing process. The routing process may include: receiving the first interaction; pursuant to the classifier, classifying the first interaction as being a first interaction type; determining the cost value of the first interaction as being the cost value corresponding to the first interaction type in the cost schedule; calculating for each of the agents an available capacity; and routing the first interaction to a first agent based on the available capacity of the first agent being sufficient given the cost value.