Abstract: A computer-implemented method for dynamically prioritizing inbound interactions in a digital multi-channel contact center. The computer-implemented method includes for each inbound interaction via a digital channel: (i) operating an interaction analyzer module to extract one or more metadata parameters from the inbound interaction; (ii) operating a prioritization module to calculate a Digital Interaction Priority Score (DIPS) of the inbound interaction based on the one or more metadata parameters; and (iii) forwarding the DIPS to an interaction distribution module to route the inbound interaction to an agent based on the DIPS. The DIPS is periodically updated until the interaction is assigned to the agent.

Abstract: Methods and systems for digital scheduling include periodically determining, from a datastore of agent profiles, a set of agents which satisfy a predefined time-off criterion; and notifying, via a digital message, one or more agents of the determined set of agents of a recommended list of dates on which to take a time-off, wherein the recommended list of dates is generated in accordance with staffing prediction data for the dates.

Abstract: Systems and methods for digital scheduling, include periodically checking a data storage for queued schedule trade requests; identifying two corresponding queued schedule trade requests; else, if two corresponding queued schedule trade requests are not identified: identifying a set of cyclic queued schedule trade requests; else, if a set of cyclic queued schedule trade requests are not identified: repeating the step of periodically checking; approving or rejecting the identified schedule trade requests based on one or more approval criteria; and if the identified schedule trade requests were approved, outputting one or more updated schedules reflecting the approved schedule trade requests.

Abstract: A computerized system and method may calculate or update task or job execution schedules for a plurality of resources and perform automated actions based on the calculated or updated schedules. A computerized system including one or more processors, a memory, and a communication interface to communicate via a communication network with remote computing devices, may be used for forecasting or reforecasting task properties for relevant time intervals, where the properties may describe future tasks to be handled by a plurality of resources; calculating an allocation matrix for the time intervals based on the predicted properties; and calculating or updating a schedule based on the calculated allocation matrix—for example to automatically extend a break for one or more resources, where resources are not to handle tasks during the break. Some embodiments of the invention may perform, e.g., computer automated actions based on calculated or updated schedules.

Abstract: A computerized system and method may provide automated clustering procedures where each clustered entity or node may be included in a plurality of clusters (e.g., more than a single cluster). Clustering procedures provided by some embodiments of the invention may involve measuring and/or quantifying degrees of relevance and/or generality for a plurality of entities or nodes. In some embodiments, a clustering procedure may be used, e.g., to generate a hierarchical, multi-tiered taxonomy of such entities. A computerized system comprising a processor, and a memory, may be used for ranking a plurality of nodes; select nodes based on the ranking; cluster selected nodes into intermediate clusters; calculate distances between unselected nodes and intermediate clusters; and cluster unselected nodes and intermediate clusters into final clusters based on the calculated distances.

Abstract: A system and a method for managing interactions between agent devices and customer devices, the system comprising: a computing device; a local storage; a memory; and a processor, the processor configured to: identify interaction data in interactions between an agent device and a customer device that show a transition from a first connection type to a second connection type; and when a transition in connection types is identified, initiating one or more remedial measures.

Abstract: A system and a method of managing data transfer for a plurality of data centers may include identifying data transfer capacity and data transfer demand for each server of a plurality of data centers; calculating a data transfer distribution for the plurality of data centers that prioritizes data transfer between servers of a first data center of the plurality of data centers over data transfer between servers of the first data center and servers of the remaining data centers of the plurality of data centers based on the identified data transfer capacity and the data transfer demand; and allocating data transfers to the servers of the plurality of data centers.

Abstract: A method for allocating resources for a plurality of time intervals, including: receiving a forecasted workload and at least one required service metric value; applying a search algorithm to identify an initial allocation assignment; inputting the assignment to a machine learning algorithm, the machine learning algorithm trained on historic data of past intervals; predicting an expected service metric value provided by the initial allocation assignment; adjusting the initial allocation assignment based on a difference between the expected service metric value and the corresponding required service metric value; iteratively repeating the applying, inputting, predicting, and adjusting operations until one of: the expected service metric value predicted for an adjusted allocation assignment is within a predetermined distance of the corresponding at least one required service metric value for the interval; or a predetermined time has elapsed.

Abstract: A system and method for real-time fraud detection with a social engineering phoneme (SEP) watchlist of phoneme sequences may perform real-time fraud prevention operations including receiving incoming call interactions and grouping the call interactions into one or more clusters, each cluster associated with a speaker's voice based on voiceprints. For a pair of voiceprints in a cluster, a phoneme sequence is extracted for each voice print. From the extracted phoneme sequences, a similarity score is then calculated to determine if a match exists between the extracted phoneme sequences based on a threshold. If determined a match exists, the phoneme sequence may be added to a SEP watchlist.

Abstract: Embodiments are disclosed for securing internet-based transfer of voice call data. Embodiments may include: sending a primary-protocol-encoded communication, by a forwarding unit (FU), to a session border controller (SBC), when an indication is received at the FU that a secondary-protocol-encoded communication has been received at a gateway component, from a voice call data source, to propose transferring voice call data to the SBC; outputting by the SBC, in response to the primary-protocol-encoded communication an IP address encoded with the primary protocol; converting, by a gateway component, the IP address encoded with the primary protocol into an IP address encoded with the secondary protocol; and sending, by a gateway component, the IP address encoded with the secondary protocol to the voice call data source that is proposing to transfer the voice call data.

Abstract: A method of managing interaction recordings of an interaction between agent devices and customer devices, the method comprising: initiating an interaction recording of the interaction between an agent device and a customer device, wherein the interaction recording comprises metadata items; storing one or more parts of the interaction recording in a local storage; identifying parts of the interaction recording whose metadata items fulfill archiving criteria; and archiving parts of the interaction recording stored in the local storage whose metadata items fulfill the archiving criteria and deleting parts of the interaction recording from the local storage whose metadata items do not fulfill the archiving criteria.

Abstract: Methods and systems for digital scheduling include, using a processor: identifying a set of target agents associated with a corresponding set of shift parameters that satisfy a set of preferences of a multi-day trade request initiated by a source agent; sending the multi-day trade request to a sub-set of the identified target agents selected by the source agent; and if a first target agent of the sub-set accepts the multi-day trade request, and if the multi-day trade request satisfies a pre-defined set of approval criteria, then automatically approving the multi-day trade request between the source agent and said first target agent, and automatically adjusting a schedule of the source agent and the first target agent to reflect the approved multi-day trade request; else: automatically rejecting the multi-day trade request.

Abstract: A computerized system and method may provide a robust, automated clustering procedure, including handling of outlier points, which may involve measuring and/or quantifying degrees of relevance and/or generality for a plurality of input entities. In some embodiments, a clustering procedure may be used, e.g., to generate a hierarchical, multi-tiered taxonomy of such entities. In some embodiments, a computerized system comprising a processor, and a memory, may be used for calculating a distance between nodes for each of a plurality of pairs of nodes, where the pairs may comprise a plurality of input entities and/or initial clusters; selecting one or more of the pairs based on the calculated distances; and merging one or more of the selected pairs, which may include a common node, into one or more final clusters. Some embodiments of the invention may allow routing interactions between remotely connected computer systems based on an automatically generated taxonomy.

Abstract: A system is provided for a cloud computing environment that is adapted to perform data processing and tracking of agent data between cloud computing tenants. The system includes a processor and a computer readable medium operably coupled thereto, to perform operations which include determining a unique identifier (ID) for an agent of the cloud computing tenants, accumulating, over a time period, agent data for the agent, refining the agent data to curated data views for the agent data based on a plurality of aggregate reports for each of a plurality of KPIs in the agent data, determining a batch processing job for the refined agent data, calculating, using the batch processing job, a base asset value (BAV) score for the agent, and updating a profile for the agent associated with the unique ID based on the calculated BAV score.

Abstract: Systems and methods are provided for configuring a set of one or more contact centers, the set of one or more contact centers associated with a total number of agents and a number of regions. The systems and methods may include predicting or selecting a number of scheduling units or an optimal number of skills for the set of one or more contact centers based on the total number of agents and the number of regions.

Abstract: Systems and methods for detecting stamps include if at least one regular shape in an image of a document is detected then outputting said at least one regular shape as a stamp; else: removing at least one of text, lines, and noise in the image of the document; and if at least one closed shape is remaining in the image of the document, then inscribing said at least one closed shape and outputting said at least one inscribed closed shape as a stamp; else if at least one open shape is remaining in the image of the document, then enclosing said at least one open shape and outputting said at least one enclosed shape as a stamp.

Abstract: A system for supporting effective campaign management in a cloud-based contact center platform. The system includes a campaign analytics engine. The campaign analytics engine includes retrieving campaign offerings of a running campaign; retrieving time-stamped text transcripts of interactions of agents of the running campaign; parsing the retrieved time-stamped text transcripts of interactions to yield parsed transcripts and related customer sentiment; comparing the yielded parsed transactions with the retrieved campaign offerings to generate analytical data. The generated analytical data includes at least one of: (i) agent campaign delivery effectiveness score; and (ii) probability of conversion. When an agent has an agent campaign delivery effectiveness score below a first threshold excluding the agent from the running campaign and sending the campaign delivery effectiveness score of the agent along with agent details and a preconfigured training list to be assigned to the agent by a QM application.

Abstract: A computerized system and method may process and predict stress levels for audio data using a machine learning based framework. A computerized system including a processor and a memory may calculate a buffer length based on a plurality of audio attributes (e.g., of a given audio input or data item), extract an audio buffer from an audio data item based on the calculated length, and predict, using a machine learning model, a stress level for the audio buffer or data item. Some embodiments of the invention may include extracting a buffer of a length determined dynamically for different audio inputs, e.g., to ensure coherency between audio attributes or features extracted from different audio inputs having different audio characteristics. In some embodiments, audio features which may be considered by the model may include, e.g., a plurality of gradients between mel-frequency cepstrum coefficients computed for relevant audio buffers or inputs.

Abstract: Coaching systems and methods, and non-transitory computer readable media, include analyzing an agent's interactions to identify knowledge gaps and specific topics where an agent has difficulties. An algorithm uses bootstrap sampling to verify that an agent's scores are significantly different from other agents' scores. The algorithm further uses a mutual information score to find topics that are associated with interactions having a high knowledge gap score.

Abstract: A computerized system and method may automatically generate a hierarchical, multi-tiered taxonomy based on measuring and/or quantifying degrees of generality for a plurality of input entities. In some embodiments of the invention, a computerized system comprising a processor, and a memory including a plurality of entities such as documents or text files, may be used for extracting words from a plurality of documents; calculating generality scores for the extracted words; selecting some of the extracted words as exemplars based on the scores; and clustering unselected words under appropriate exemplars to produce or output a corresponding taxonomy. Some embodiments of the invention may allow categorizing interactions among remotely connected computers using a domain taxonomy, and routing interactions between remotely connected computer systems based on the taxonomy.