Abstract: An example method is provided for encoding text for language processing. The method may be executed by a processing system, and the method includes receiving text comprising a plurality of alphanumeric characters or symbols and converting the text into a numerical vector comprising a plurality of numerical values, by mapping each alphanumeric character or symbol of the text to a vertex coordinate of one of a plurality of vertices of a hypercube, wherein a number of the plurality of vertices is equal to or greater than a number of the plurality of alphanumeric characters or symbols, wherein the numerical vector consumes less space in memory than the text. An amount of time consumed by language processing of the numerical vector may be less than an amount of time consumed by language processing of the text.

Abstract: A method for minimizing algorithmic bias in machine learning models includes generating, using a first machine learning model, a first output representing a prediction, where the first output is generated in response to a first plurality of inputs including sensitive features and non-sensitive features, generating, using a second machine learning model, a second output that minimizes an influence of an algorithmic bias in the first output, where the second output is generated in response to a second plurality of inputs including the non-sensitive features and the first output, and generating a recommendation related to the prediction based on the second output.

Abstract: A processing system including at least one processor may generate a plurality of subsequences of a time series data set, convert the plurality of subsequences to a plurality of frequency domain point sets, compute pairwise distances of the plurality of frequency domain point sets, project the plurality of frequency domain point sets into a lower dimensional space in accordance with the pairwise distances, where the projecting maps each of plurality of frequency domain point sets to a node of a plurality of nodes in the lower dimensional space, and generate a notification of at least one isolated node of the plurality of nodes, where the at least one isolated node represents at least one anomaly in the time series data set.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for proactively adjusting the infrastructure of a communications network in response to reporting of real-time network performance. For instance, in one example, a method includes obtaining real-time network performance metrics directly from a user endpoint device operated by a customer of a telecommunication service provider network, correlating the real-time network performance metrics with data from another data source, wherein the data includes data other than network performance metrics, and adjusting an infrastructure of the telecommunication service provider network in response to an insight gleaned through the correlating.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for proactively adjusting the infrastructure of a communications network in response to reporting of real-time network performance. For instance, in one example, a method includes obtaining real-time network performance metrics directly from a user endpoint device operated by a customer of a telecommunication service provider network, correlating the real-time network performance metrics with data from another data source, wherein the data includes data other than network performance metrics, and adjusting an infrastructure of the telecommunication service provider network in response to an insight gleaned through the correlating.

Abstract: An example method is provided for encoding text for language processing. The method may be executed by a processing system, and the method includes receiving text comprising a plurality of alphanumeric characters or symbols and converting the text into a numerical vector comprising a plurality of numerical values, by mapping each alphanumeric character or symbol of the text to a vertex coordinate of one of a plurality of vertices of a hypercube, wherein a number of the plurality of vertices is equal to or greater than a number of the plurality of alphanumeric characters or symbols, wherein the numerical vector consumes less space in memory than the text. An amount of time consumed by language processing of the numerical vector may be less than an amount of time consumed by language processing of the text.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for proactively adjusting the infrastructure of a communications network in response to reporting of real-time network performance. For instance, in one example, a method includes obtaining real-time network performance metrics directly from a user endpoint device operated by a customer of a telecommunication service provider network, correlating the real-time network performance metrics with data from another data source, wherein the data includes data other than network performance metrics, and adjusting an infrastructure of the telecommunication service provider network in response to an insight gleaned through the correlating.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for proactively adjusting the infrastructure of a communications network in response to reporting of real-time network performance. For instance, in one example, a method includes obtaining real-time network performance metrics directly from a user endpoint device operated by a customer of a telecommunication service provider network, correlating the real-time network performance metrics with data from another data source, wherein the data includes data other than network performance metrics, and adjusting an infrastructure of the telecommunication service provider network in response to an insight gleaned through the correlating.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for proactively adjusting the infrastructure of a communications network in response to reporting of real-time network performance. For instance, in one example, a method includes obtaining real-time network performance metrics directly from a user endpoint device operated by a customer of a telecommunication service provider network, correlating the real-time network performance metrics with data from another data source, wherein the data includes data other than network performance metrics, and adjusting an infrastructure of the telecommunication service provider network in response to an insight gleaned through the correlating.

Abstract: Concepts and technologies are disclosed herein for providing a location sharing service. A server computer executing a location sharing service can identify a presenter for a location sharing session and a participant in the location sharing session. The server computer can receive location information from the presenter. The location information can identify a location accessed at a computing device associated with the presenter during a conference. The server computer can provide the location information to a user device associated with the participant during the conference. The server computer also can provide a log including the location information to the user device during or after the conference.

Abstract: Concepts and technologies are disclosed herein for providing a location sharing service. A server computer executing a location sharing service can identify a presenter for a location sharing session and a participant in the location sharing session. The server computer can receive location information from the presenter. The location information can identify a location accessed at a computing device associated with the presenter during a conference. The server computer can provide the location information to a user device associated with the participant during the conference. The server computer also can provide a log including the location information to the user device during or after the conference.