Abstract: Methods and systems for data management include representing, organizing, and accessing very large data sets. Embodiments describe supporting data sets of various size based on attributed data slices (ADSs) to enable reduced memory requirements, query decomposition and parallel execution, and constant execution times for concurrent queries. The ADSs can include data buckets comprising items that are grouped by an attribute key. Attribute groups can be further sorted (e.g., in ascending order) based on the attribute key. According to some embodiments, the essential structure of an ADS provides additional functionality while preserving the behavior expected of an ADS through the use of an Extension Block containing attribute location data.

Abstract: Methods and systems for data management include representing, organizing, and accessing very large data sets. Embodiments describe supporting data sets of various size based on attributed data slices (ADSs) to enable reduced memory requirements, query decomposition and parallel execution, and constant execution times for concurrent queries. The ADSs can include data buckets comprising items that are grouped by an attribute key. Attribute groups can be further sorted (e.g., in ascending order) based on the attribute key. According to some embodiments, the essential structure of an ADS provides additional functionality while preserving the behavior expected of an ADS through the use of an Extension Block containing attribute location data.

Abstract: Methods and systems for data management include representing, organizing, and accessing very large data sets. Embodiments describe supporting data sets of various size based on attributed data slices (ADSs) to enable reduced memory requirements, query decomposition and parallel execution, and constant execution times for concurrent queries. The ADSs can include data buckets comprising items that are grouped by an attribute key. Attribute groups can be further sorted (e.g., in ascending order) based on the attribute key. According to some embodiments, the essential structure of an ADS provides additional functionality while preserving the behavior expected of an ADS through the use of an Extension Block containing attribute location data.

Abstract: Methods and systems for data management include representing, organizing, and accessing very large data sets. Embodiments describe supporting data sets of various size based on attributed data slices (ADSs) to enable reduced memory requirements, query decomposition and parallel execution, and constant execution times for concurrent queries. The ADSs can include data buckets comprising items that are grouped by an attribute key. Attribute groups can be further sorted (e.g., in ascending order) based on the attribute key. According to some embodiments, the essential structure of an ADS provides additional functionality while preserving the behavior expected of an ADS through the use of an Extension Block containing attribute location data.

Abstract: Systems and methods for tagging data strings in electronic documents using a convolutional neural network model. The method includes receiving an electronic document and extracting data strings from the electronic document. The method also includes tokenizing each of the data strings into tokens and determining a first tag corresponding to a first token for a first data string using a convolutional neural network model. The method further includes receiving user response data corresponding to an accuracy of the first tag and determining a second tag corresponding to the first token based on the user response data using the convolutional neural network model. The method also includes storing results data into a database and generating for display the results data on a user device.

Abstract: A system and method for fraud detection and management are provided. The system includes a first communication device that receives a phone call from a second communication device, wherein a call flow of the phone call comprises one or more distinct phases. The system also includes a fraud detection and management system (FDMS) platform that determines whether the phone call exceeds a predetermined risk threshold at each distinct phase of the call flow.

Abstract: A system and method for fraud detection for a telephony platform based on an analysis of call detail records (CDRs) that are generated by the telephony platform. The analysis is based on collecting, organizing, transforming, analyzing, and quantifying the CDR data into a plurality of data analytics and data correlations and then applying fuzzy logic to the data analytics to generate a fraud risk rating for each incoming call into the platform.

Abstract: A system and method for fraud detection and management are provided. The system includes a first communication device that receives a phone call from a second communication device, wherein a call flow of the phone call comprises one or more distinct phases. The system also includes a fraud detection and management system (FDMS) platform that determines whether the phone call exceeds a predetermined risk threshold at each distinct phase of the call flow.

Abstract: A system and method for fraud detection for a telephony platform based on an analysis of call detail records (CDRs) that are generated by the telephony platform. The analysis is based on collecting, organizing, transforming, analyzing, and quantifying the CDR data into a plurality of data analytics and data correlations and then applying fuzzy logic to the data analytics to generate a fraud risk rating for each incoming call into the platform.

Abstract: A system and method for fraud detection for a telephony platform based on an analysis of call detail records (CDRs) that are generated by the telephony platform. The analysis is based on collecting, organizing, transforming, analyzing, and quantifying the CDR data into a plurality of data analytics and data correlations and then applying fuzzy logic to the data analytics to generate a fraud risk rating for each incoming call into the platform.

Abstract: Systems, methods and apparatus are described herein for continuously measuring voice clarity and speech intelligibility by evaluating a plurality of telecommunications channels in real time. Voice clarity and speech intelligibility measurements may be formed from chained, configurable DSPs that can be added, subtracted, reordered, or configured to target specific audio features. Voice clarity and speech intelligibility may be enhanced by altering the media in one or more of the plurality of telecommunications channels. Analytics describing the measurements and enhancements may be displayed in reports, or in real time via a dashboard.

Abstract: A method for improving a call-participant behavior, the method includes receiving an intensity data signal and an intensity variation data signal related to an ongoing call, receiving a pitch data signal and a pitch variation data signal related to the ongoing call, receiving a tempo data signal and a tempo variation data signal related to the ongoing call, receiving a channel comparison data signal related to the ongoing call, generating a real-time call progress signal based on the intensity data signal, the intensity variation data signal, the pitch data signal, the pitch variation data signal, the tempo data signal, the tempo variation data signal, and the channel comparison data signal, and sending the real-time call progress signal to a user device.