Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of measuring interactive content data polarity. The system records interactive communications and stores the interactive communications as interactive content files. Natural language processing technology is used to determine a polarity score for each interactive content data file, and the polarity score is converted to a polarity identification. The system determines a net polarity using the proportion of interactive content files having various polarity identifications. The system also classifies the interactive content files according to polarity using a branched decision network. The system sets an overall net polarity using the polarity identification and polarity classification. The overall net polarity is tracked and displayed as a function of content metadata and sequencing data.

Abstract: Disclosed are systems and methods that automate the process of measuring interactive content data polarity. The system records interactive communications and stores the interactive communications as interactive content files. Natural language processing technology is used to determine a polarity score for each interactive content data file, and the polarity score is converted to a polarity identification. The system determines a net polarity using the proportion of interactive content files having various polarity identifications. The system also classifies the interactive content files according to polarity using a branched decision network. The system sets an overall net polarity using the polarity identification and polarity classification. The overall net polarity is tracked and displayed as a function of content metadata and sequencing data.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology. The interactive content data is converted to machine encoded communication elements that can be further grouped into machined encoded n-grams. The co-occurrence of machine encoded communication elements or n-grams in the interactive content data is compared against communication elements or n-grams in a seed set of concentrated content files to determine an equivalence value. In this manner, the system can automate the process of determining the equivalence of interactive content data files.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology. The interactive content data is converted to machine encoded communication elements that can be further grouped into machined encoded n-grams. The co-occurrence of machine encoded communication elements or n-grams in the interactive content data is compared against communication elements or n-grams in a seed set of concentrated content files to determine an equivalence value. In this manner, the system can automate the process of determining the equivalence of interactive content data files.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology. The interactive content data is converted to machine encoded communication elements that can be further grouped into machined encoded n-grams. The co-occurrence of machine encoded communication elements or n-grams in the interactive content data is compared against communication elements or n-grams in a seed set of concentrated content files to determine an equivalence value. In this manner, the system can automate the process of determining the equivalence of interactive content data files.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: Properties of a solid state drive can be shown in a visual representation, which includes aspects of the solid state drive, such as remaining lifetime, read and write workload, life acceleration characteristics, and temperature correlation of data and errors.

Abstract: Data, such as indicators of storage devices, are logged periodically with the recorded time. The time logged data, e.g., data collected at different times, can be used to calculate properties and characteristics of the storage devices, including instantaneous properties and time evolution properties.