Abstract: A service provider computing system includes memory having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to obtain a first set of complaint logs corresponding to one or more user complaints, each complaint log including a resolution comments field providing a textual representation of a resolution for a corresponding complaint log, parse the resolution comments field of each complaint log of the first set of complaint logs to identify one or more key terms, and execute a machine-learning predictive model using the one or more key terms to generate, for each complaint log, a prediction indicating whether a corresponding complaint should have compensation, the machine-learning predictive model being a supervised machine learning model configured to accept the parsed resolution comments field for the first set of complaint logs as inputs and to output the prediction for each complaint log.

Abstract: The present disclosure describes devices and methods of providing a technology environment for analyzing unstructured data to generate structured data. A set of electronic documents, each electronic document associated with a type of product, may be accessed. A data instance for each of the documents may be generated. The data instance may include a plurality of data fields that are based on the type of product. The electronic documents may be analyzed to identify values for each of the plurality of data fields. Analyzing the electronic documents may comprise applying a respective character recognition algorithm to respective electronic documents, and assigning a confidence factor to each of the values. The data instances comprising the values for each of the plurality of data fields may be stored in a second database.

Abstract: The present disclosure describes devices and methods of providing a technology environment for analyzing unstructured data to generate structured data. A set of electronic documents, each electronic document associated with a type of product, may be accessed. A data instance for each of the documents may be generated. The data instance may include a plurality of data fields that are based on the type of product. The electronic documents may be analyzed to identify values for each of the plurality of data fields. Analyzing the electronic documents may comprise applying a respective character recognition algorithm to respective electronic documents, and assigning a confidence factor to each of the values. The data instances comprising the values for each of the plurality of data fields may be stored in a second database.

Abstract: The present disclosure describes devices and methods of providing a technology environment for analyzing unstructured data to generate structured data. A set of electronic documents, each electronic document associated with a type of product, may be accessed. A data instance for each of the documents may be generated. The data instance may include a plurality of data fields that are based on the type of product. The electronic documents may be analyzed to identify values for each of the plurality of data fields. Analyzing the electronic documents may comprise applying a respective character recognition algorithm to respective electronic documents, and assigning a confidence factor to each of the values. The data instances comprising the values for each of the plurality of data fields may be stored in a second database.

Abstract: A service provider computing system includes memory having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to obtain a first set of complaint logs corresponding to one or more user complaints, each complaint log including a resolution comments field providing a textual representation of a resolution for a corresponding complaint log, parse the resolution comments field of each complaint log of the first set of complaint logs to identify one or more key terms, and execute a machine-learning predictive model using the one or more key terms to generate, for each complaint log, a prediction indicating whether a corresponding complaint should have compensation, the machine-learning predictive model being a supervised machine learning model configured to accept the parsed resolution comments field for the first set of complaint logs as inputs and to output the prediction for each complaint log.

Abstract: A service provider computing system includes memory having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to obtain a first set of complaint logs corresponding to one or more user complaints, each complaint log including a resolution comments field providing a textual representation of a resolution for a corresponding complaint log, parse the resolution comments field of each complaint log of the first set of complaint logs to identify one or more key terms, and execute a machine-learning predictive model using the one or more key terms to generate, for each complaint log, a prediction indicating whether a corresponding complaint should have compensation, the machine-learning predictive model being a supervised machine learning model configured to accept the parsed resolution comments field for the first set of complaint logs as inputs and to output the prediction for each complaint log.

Abstract: Methods, systems, and storage media for robust monitoring a gauge are disclosed herein. In an embodiment, a digital image of a gauge may be received to identify an analog value indicator of the gauge and to form an indicator representation corresponding to the analog value indicator. Robust optical character recognition and image filter may provide enhanced gauge reading and/or monitoring. Other embodiments may be disclosed and/or claimed.

Abstract: In various embodiments, an angular gauge reporting system (“AGRS”) may determine one or more values from an image of an angular gauge. The AGRS may receive one or more images of the gauge and develop an angular map to determine values indicated by the gauge. The AGRS may identify numbers in the image to generate the angular map. The AGRS may determine a center for the angular gauge. The AGRS may determine numerical values by processing capture images of the angular gauge though angular or linear interpolation of values. By generating the angular map prior to later determination of values, the AGRS may provide for determination of numerical values without requiring repetition of actions which may be computationally complex or resource intensive. Other embodiments may be described and/or claimed.

Abstract: Methods, systems, and storage media for robust monitoring a gauge are disclosed herein. In an embodiment, a digital image of a gauge may be received to identify an analog value indicator of the gauge and to form an indicator representation corresponding to the analog value indicator. Robust optical character recognition and image filter may provide enhanced gauge reading and/or monitoring. Other embodiments may be disclosed and/or claimed.

Abstract: In various embodiments, an angular gauge reporting system (“AGRS”) may determine one or more values from an image of an angular gauge. The AGRS may receive one or more images of the gauge and develop an angular map to determine values indicated by the gauge. The AGRS may identify numbers in the image to generate the angular map. The AGRS may determine a center for the angular gauge. The AGRS may determine numerical values by processing capture images of the angular gauge though angular or linear interpolation of values. By generating the angular map prior to later determination of values, the AGRS may provide for determination of numerical values without requiring repetition of actions which may be computationally complex or resource intensive. Other embodiments may be described and/or claimed.