Abstract: A system and method for accessing elements of a table in a digital image of the table, including: obtaining the digital image of the table; finding table elements in the digital image based on digital table properties, wherein the table elements define table cells; calculating coordinates of the table cells in the digital image based on the table elements; and accessing content of a selected table cell in the digital image using the coordinates of the selected table element.

Abstract: A system is provided for fraud prevention upscaling with a fraudster voice print watchlist. The system includes a processor and a computer readable medium operably coupled thereto, to perform fraud prevention operations which include receiving a first voice print of a user during a voice authentication request, accessing the fraudster voice print watchlist comprising voice print representatives for a plurality of voice print clusters each having one or more of a plurality of voice prints identified as fraudulent for a voice biometric system, determining that one or more of the voice print representatives in the fraudster voice print watchlist meets or exceeds a first biometric threshold for risk detection of the first voice print during the fraud prevention operations, and determining whether the first voice print matches a first one of the plurality of voice print clusters.

Abstract: A computerized-method for gauging agent's self-assessment effectiveness, is provided herein. The computerized-method includes for each interaction (i) operating a Self-assessment Consolidation module to calculate a confidence-interval for each data-point of one or more preconfigured data-points, and (ii) operating a Self-assessment Divergence Determinant (SDD) module. The operating of the SDD includes: retrieving one or more data-points of the interaction; for each data-point retrieving the confidence interval; setting a divergence-indicator as zero, when the data point is within the confidence-interval; setting the divergence-indicator as a subtraction of the data point from the calculated lower-bound, when the data-point is lower than the lower-bound of the confidence-interval; and setting the divergence-indicator as a subtraction of the calculated upper-bound from the data-point, when the data-point is greater than the upper-bound of the confidence-interval.

Abstract: A computerized system and method may determine the recording and/or storing and/or deleting of data items received from remotely connected computer systems, which may be for example interaction recordings associated with a plurality of agents as part of their activity within a given system or organization, using a supervised classification machine learning based approach. A computerized system comprising one or more processors, a communication interface to communicate via a communication network with remote computing devices, and a memory including a data store of a plurality of data items, may be used for extracting features from a plurality of data items; predicting evaluation likelihood values based on the features; deriving storing percentages for a plurality of remote computing devices; and, based on likelihood values and storing percentages, recording and/or storing and/or deleting a plurality of data items from a data store or database.

Abstract: Securely sharing proof of knowledge of information without revealing the information, for example to allow an institution to prove it has knowledge regarding an alert. Code or software may be generated (at a first computer system) which takes as input one or more details regarding an entity and returns a value based on a match to one or more actual details regarding the entity. A name may be generated for the code based on information describing the entity, and the code may be published to a blockchain, along with at least one key corresponding to the code. For each name an entry may be creating in an index, converting the name to a blockchain address. A proof based on the code may be generated at a second computer system, which, if verified, results in the first institution and the second institution sharing information regarding the entity.

Abstract: A computerized-method for providing an elastic media forking infrastructure to cloud distributed real-time applications, is provided herein. In a network having a direct media streaming between a first media-client and a source device, in a direct media streaming mode, upon receiving a request from a second media-client, via a signaling protocol, to receive media from the source device, switching from the direct media streaming mode to a media forking mode by starting a media forking service on a media forking infrastructure. Upon receiving a request from the second media-client to terminate media reception from the source device, switching from media forking mode to direct streaming mode, by ending the media forking service, and operating the direct media streaming between the first media-client and the source device.

Abstract: A computer based system and method for automatically detecting frustration in an interaction, may include: identifying in the interaction using a set of linguistic rules, natural language patterns related to frustration, wherein the linguistic rules further define weights associated with the natural language patterns and rule metadata; reviewing the rule metadata associated with the identified natural language patterns to identify override attributes, wherein if the rule metadata does not include override attributes, then a frustration level in the interaction is determined based on the identified natural language patterns and weights associated with the identified natural language patterns; and if the rule metadata includes override attributes than the frustration level is determined based on the identified override attributes.

Abstract: Systems and methods for monitoring a quality of interactions include: receiving one or more quality metrics relating to one or more quality targets; determining, on a periodic basis, a current quality value for each of the one or more quality targets; calculating a deviation of the current quality value from a desired value of the quality target; weighting the one or more quality targets according to the calculated deviation; and determining a set of one or more interactions for review based on one or more quality metric deviations and the weighted quality targets.

Abstract: Systems for and methods of determining the priority of a call interaction include receiving a call interaction from a call center; validating, by a validation and transcription engine, that the call interaction is authentic; converting, by the validation and transcription engine, the call interaction into text; calculating, by the data calculation engine, a priority of the call interaction from the text and organization, location, and time information in the text by determining an important of words in the text and correlating the words to a priority class using a pre-trained algorithm that is trained on emergency-type and emergency services-type language; determining that the call interaction should be transmitted to the call center for initial handling by a call center agent; and transmitting the call interaction, the calculated priority, and the extracted information to the call center.

Abstract: Traffic routing and infrastructure scaling systems and methods, and non-transitory computer readable media, including receiving, by a primary region, incoming customer requests; determining, by a traffic control module, a traffic redirect quotient (TRQ) and a regional scale quotient (RSQ), wherein the TRQ indicates a percentage of the incoming customer requests needed to be redirected to a secondary partner region and the RSQ indicates a percentage of infrastructure scaling needed in the secondary partner region; receiving, by a recommendation processing module, the TRQ and the RSQ; automatically initiating, by the recommendation processing module, redirection of the percentage of the incoming customer requests indicated by the TRQ to the secondary partner region, scaling the percentage of infrastructure indicated by the RSQ in the secondary partner region, or both; and routing, by a network traffic manager service, the percentage of the incoming customer requests indicated by the TRQ to the secondary partner

Abstract: A data storage system configured to optimize selection of a plurality of data storage devices. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium including a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform storage device selection operations which include detecting and gathering storage device information for storing data recordings to the plurality of data storage devices, determining, by a storage load balancer, a plurality of storage efficiency scores for the plurality of data storage devices using a loss function and the gathered storage device information, generating a storage efficiency table, and assigning, by the storage load balancer, a first data recording to one of the plurality of data storage devices based on the storage efficiency table and an efficiency score threshold for the plurality of storage efficiency scores.

Abstract: There is thus provided a computerized-method for calculating a Repeated-Information-Request (RIR) score of an interaction in a contact center, by which a related interaction-recording is filtered for evaluation. The computerized-method is operating in a computerized-system which includes a processor, a data-storage and a memory to store the data-storage. The processor is operating a RIR score calculation module. The operating of the RIR score calculation module includes: (i) retrieving from the data-storage an interaction-recording and an interaction-recording-length thereof; (ii) operating a module on the retrieved interaction-recording to count a number of requests to repeat information; (iii) calculating a RIR score according to the number of requests to repeat information and the interaction-recording-length; and (iv) storing the RIR score of the retrieved interaction-recording in the data-storage.

Abstract: Some aspects of the invention may include a computer-implemented method for enrolling voice prints generated from audio streams, in a database. The method may include receiving an audio stream of a communication session and creating a preliminary association between the audio stream and an identity of a customer that has engaged in the communication session based on identification information. The method may further include determining a confidence level of the preliminary association based on authentication information related to the customer and if the confidence level is higher than a threshold, sending a request to compare the audio stream to a database of voice prints of known fraudsters. If the audio stream does not match any known fraudsters, sending a request to generate from the audio stream a current voice print associated with the customer and enrolling the voice print in a customer voice print database.

Abstract: A system and method may adjust the threshold or other settings in a biometric comparison system, or provide a report or display of parameters. Over a series of comparisons of authentication biometric samples (e.g. authentication VPs) to enrollment biometric samples (e.g. enrollment VPs), the authentication samples may be stored, and scores resulting from the biometric comparisons may be stored in a first set of scores. A second set of biometric comparisons may be created, each using a pairing of a stored authentication biometric sample and an enrollment biometric sample, each biometric comparison resulting in a score, the scores forming a second set of scores. The first and second sets of scores may be combined to produce a third set of scores, and an iterative process may be performed over the third set of scores to update the parameters of the Gaussian distribution of the third set of scores.

Abstract: A system and method may identify computer-based processes which may be candidates for automation. Embodiments may involve a semi-supervised approach for identifying processes as automation opportunities. Transition probabilities for pairs of routines within a candidate process may be calculated based on a set of instances of the process (e.g., in a dataset of computer actions) using a dynamic time-window optimization procedure, where transition times may be measured for a plurality of instances of a first and second routines of a given pair of routines, and where statistical distributions may be calculated and used for deriving one or more time windows, describing a predetermined percentile (e.g., the 70th percentile) of the measured transitions and used for estimating a transition probability for the pair of routines. In some embodiments, the input set of transitions and routines may be generated by a user or business analyst using a graphical user interface (GUI).

Abstract: A system and method for calculating a journey excellence score (JES) for a customer journey in a contact center, including, during a training phase: representing each of a plurality of tagged customer journeys by a list of attributes and a value associated with each of the attributes, wherein each of the tagged customer journeys is tagged with respect to a dissatisfaction indicator, and training a model using the plurality of tagged customer journeys, based on the associated values and tags, to generate model weights; and at runtime: obtaining the customer journey; representing the customer journey by the list of attributes and a value associated to each of the attributes; and calculating the JES for the customer journey by applying the model weights to the associated values.

Abstract: A system and method may identify computer-based processes involving the use of text templates which may be candidates for automation. Using one or more computers, embodiments of the invention may sort low-level user action information for a given process which may be received as input; search for a plurality of strings pasted multiple times in the sorted information; discard one or more of the strings found from the search which correspond to a set of criteria (e.g., found to be shorter, or pasted, or edited fewer times than a predetermined threshold); group the strings according to an identifier of the target app where each string was pasted; iteratively calculate a similarity score for strings or groups of strings, and cluster strings or groups for which the similarity score is below a predetermined threshold, to form final clusters; and suggest the final clusters as automation opportunities to, e.g., a business analyst.

Abstract: A computer based system and method for automatically transmitting an electronic notice to a publisher of negative content, that includes: monitoring at least one electronic social media channel to identify content that is relevant to an entity; analyzing the identified content to identify content with negative sentiment, and an identity of the publisher of the content with the negative sentiment; and initiating an automated interaction with the publisher. Initiating the interaction may include posting an automatic reply to a message in the electronic social media channel that includes the content with the negative sentiment and/or initiating an automatic phone call.

Abstract: A computerized-method using a cloud-based computing environment for improving client service, in a contact center is provided herein. The computerized-method includes: retrieving a context of a query and a time-limit from a CTI event and attempting to retrieve data to evaluate average resolution time for the received context. When the data is found, comparing the evaluated average resolution time with the received time-limit and when the received time-limit is below the evaluated average resolution time, sending a delay notice and providing the client a menu of options for querying through other channels. When the data is not found, or when the received time-limit is above the evaluated average resolution time, presenting on an agent dashboard, the time-limit of the client and accordingly updating parameters in the agent dashboard during the inbound call, thus, improving client service, by considering the time-limit of the client before the agent addresses a query.

Abstract: A computer-implemented method for analyzing call interactions in an interactions database by a Proactive Fraud Exposure (PFE) engine is provided herein. The computer-implemented method may generate a voiceprint for each call interaction; (ii) use a machine learning technique to group the call interactions into one or more clusters based on respective voiceprints in the voiceprints database; (iii) store the one or more clusters; and (iv) rank and classifying the one or more clusters to yield a list of potential fraudsters. The computer-implemented method may further transmit the list of potential fraudsters to a user to enable the user to review said list of potential fraudsters and to add fraudsters from the list to a watchlist database.