Abstract: A device, system, and method are provided for detecting an email phishing attack by training graph neural network to detect phishing emails based on hypertext markup language (HTML) tags and cascading style sheets (CSS) included in an email. Noise is added during the training of the graph neural network to make the trained graph neural networks more robust against small changes in the training data.

Abstract: A system is provided to categorize voice prints during a voice authentication. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice authentication operations which include receiving an enrollment of a user in the biometric authentication system, requesting a first voice print comprising a sample of a voice of the user, receiving the first voice print of the user during the enrollment, accessing a plurality of categorizations of the voice prints for the voice authentication, wherein each of the plurality of categorizations comprises a portion of the voice prints based on a plurality of similarity scores of distinct voice prints in the portion to a plurality of other voice prints, determining, using a hidden layer of a neural network, one of the plurality of categorizations for the first voice print, and encoding the first voice print with the one of the plurality of categorizations.

Abstract: A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Abstract: A computer training device and method is provided for training a deep learning algorithm to classify incoming emails as belonging to one of multiple categories. The deep learning algorithm uses a loss function to avoid a low precision risk caused by a number of received emails for at least two of the multiple categories being imbalanced (e.g., by at least two orders of magnitude). The loss function compensates for the imbalance in received emails by changing depending on the criticality of the score being determined.

Abstract: A system and method for creating input data to be used to train a conversational bot may include receiving a set of conversations, each conversation including sentences, classifying each sentence into a dialog act taken from a number of dialog acts, for each set of sentences classified into a dialog act, clustering the set of sentences into clusters based on the content (e.g. text) of the sentences, each cluster having a cluster name or label, and generating a language model based on the cluster labels. Slots may be identified in the sentences based in part on the dialog act classifications. A bot may be trained using data such as the slots, language model, and clusters.

Abstract: A system is provided to predict requested playbacks of media files by users from a media storage system. The system includes a processor and a computer readable medium operably coupled thereto, to perform predictive playback operations which include accessing an AI model and a media file comprising metadata associated with generating the media file, generating a predictive score for a playback of the media file based on the AI model and the metadata, comparing the predictive score to a threshold required to transcode the media file into a playback format prior to the playback, predicting the playback based on the comparing, determining a predicted playback time of the media file based on the metadata for the media file, and transcoding the media file into the playback format prior to the predicted playback time.

Abstract: A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Abstract: A system and method for authenticating an identity may include generating a first generic representation representing a stored audio content, generating a second generic representation representing input audio content, and, providing the first and second generic representations to a voice biometrics unit adapted to authenticate an identity based on the first and second generic representations.

Abstract: A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Abstract: A computerized-method for automatically documenting automatically-discovered actions of a business-process for automation thereof is provided herein. The computerized-method includes operating a build-automation-document module. The build-automation-document module includes: (i) retrieving the set of automatically-discovered actions of the business process for automation thereof. Each action is of a related type and related to an application to complete the business process via the applications portal.

Abstract: A system is provided to categorize voice prints during a voice authentication. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice authentication operations which include receiving an enrollment of a user in the biometric authentication system, requesting a first voice print comprising a sample of a voice of the user, receiving the first voice print of the user during the enrollment, accessing a plurality of categorizations of the voice prints for the voice authentication, wherein each of the plurality of categorizations comprises a portion of the voice prints based on a plurality of similarity scores of distinct voice prints in the portion to a plurality of other voice prints, determining, using a hidden layer of a neural network, one of the plurality of categorizations for the first voice print, and encoding the first voice print with the one of the plurality of categorizations.

Abstract: A computerized-method for automatically documenting automatically-discovered actions of a business-process for automation thereof is provided herein. The computerized-method includes operating a build-automation-document module. The build-automation-document module includes: (i) retrieving the set of automatically-discovered actions of the business process for automation thereof. Each action is of a related type and related to an application to complete the business process via the applications portal.

Abstract: Systems and methods for providing unsupervised model health monitoring extract from an interaction database, first and second random samples of interaction data relating to first and second sets of interactions during first and second periods of time; score each interaction of the first and second sets of interactions by applying a predictive model to the related interaction data to produce first and second sets of interaction scores; identify a plurality of sub-populations among the first and second sets of interaction scores by applying a clustering model to the first and second sets of interaction scores; measure distances between each of the plurality of sub-populations among the first and second sets of interaction scores; compare the distances of the first period of time and the distances of the second period of time; and generate an alert when the comparison exceeds a predefined threshold.

Abstract: Methods for routing customers to an agent include receiving a customer communication; representing the customer communication as an array of one or more agent skills desired to handle the customer communication in one hot coding format or as a vector with an induced metric using an embedding algorithm; routing the represented customer communication to an agent having the one or more agent skills; measuring performance of the agent in relation to the one or more agent skills during or after the customer communication; updating, in real-time, one or more performance scores of the agent in a skill profile, wherein the one or more performance scores are related to the one or more agent skills; and routing subsequent customer communications based on the updated one or more performance scores.

Abstract: A system is provided to predict requested playbacks of media files by users from a media storage system. The system includes a processor and a computer readable medium operably coupled thereto, to perform predictive playback operations which include accessing an AI model and a media file comprising metadata associated with generating the media file, generating a predictive score for a playback of the media file based on the AI model and the metadata, comparing the predictive score to a threshold required to transcode the media file into a playback format prior to the playback, predicting the playback based on the comparing, determining a predicted playback time of the media file based on the metadata for the media file, and transcoding the media file into the playback format prior to the predicted playback time.

Abstract: A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Abstract: Methods for routing customers to an agent include receiving a customer communication; representing the customer communication as an array of one or more agent skills desired to handle the customer communication in one hot coding format or as a vector with an induced metric using an embedding algorithm; routing the represented customer communication to an agent having the one or more agent skills; measuring performance of the agent in relation to the one or more agent skills during or after the customer communication; updating, in real-time, one or more performance scores of the agent in a skill profile, wherein the one or more performance scores are related to the one or more agent skills; and routing subsequent customer communications based on the updated one or more performance scores.

Abstract: A system and method for creating input data to be used to train a conversational bot may include receiving a set of conversations, each conversation including sentences, classifying each sentence into a dialog act taken from a number of dialog acts, for each set of sentences classified into a dialog act, clustering the set of sentences into clusters based on the content (e.g. text) of the sentences, each cluster having a cluster name or label, and generating a language model based on the cluster labels. Slots may be identified in the sentences based in part on the dialog act classifications. A bot may be trained using data such as the slots, language model, and clusters.

Abstract: Methods and systems for optimization of interactive voice recognition (IVR) system processes are provided. One or more desired optimization parameters can be determined based on an IVR transaction log that includes a plurality of IVR journeys. The IVR journeys can be filtered, transformed into vectors and/or clustered.

Abstract: A method and system for evaluating the performance of individuals, such as agents in a call center, each performing multiple tasks may include obtaining a performance score for each execution of a task by individuals in the group of individuals; determining the distribution of the performance scores; comparing single performance scores with the distribution of performance scores; and selecting a single performance score for an individual based on said comparison. An oscillator algorithm may be used to determine whether said selected performance score is part of a trend in performance by that individual.