Abstract: Aspects of the disclosure relate to multicomputer systems and methods for data authentication and event execution using a blockchain approach. Any full node computing device in a network, including a data authentication and event execution computing platform, may receive data from one or more sources. The computing platform may verify the authenticity of at least one aspect of the received data. Once the authenticity of the data has been verified, the computing platform may generate a new block of a user's blockchain by cryptographically encrypting the received data, may add the new block to the user's blockchain, and may store the updated blockchain. The platform may then transmit an indication that the received data has been authenticated to the data source. In addition, the computing platform may generate a command configured to execute an action associated with the new block and may transmit the command to the data source.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine and a tagging engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to identify observed concepts within the audio file. The tagging engine is further configured to compare the observed concepts to the first set of concepts, to determine one or more observed concepts matches concepts linked with AI-defined tags, and to modify metadata for the audio file to include AI-defined tags.

Abstract: Aspects of the disclosure relate to multicomputer systems and methods for data authentication and event execution using a blockchain approach. Any full node computing device in a network, including a data authentication and event execution computing platform, may receive data from one or more sources. The computing platform may verify the authenticity of at least one aspect of the received data. Once the authenticity of the data has been verified, the computing platform may generate a new block of a user's blockchain by cryptographically encrypting the received data, may add the new block to the user's blockchain, and may store the updated blockchain. The platform may then transmit an indication that the received data has been authenticated to the data source. In addition, the computing platform may generate a command configured to execute an action associated with the new block and may transmit the command to the data source.

Abstract: Aspects of the disclosure relate to multicomputer systems and methods for data authentication and event execution using a blockchain approach. Any full node computing device in a network, including a data authentication and event execution computing platform, may receive data from one or more sources. The computing platform may verify the authenticity of at least one aspect of the received data. Once the authenticity of the data has been verified, the computing platform may generate a new block of a user's blockchain by cryptographically encrypting the received data, may add the new block to the user's blockchain, and may store the updated blockchain. The platform may then transmit an indication that the received data has been authenticated to the data source. In addition, the computing platform may generate a command configured to execute an action associated with the new block and may transmit the command to the data source.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine and a tag management engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tag management engine is configured to receive an audio file, identify tags linked with the audio file, to determine an access frequency for the audio file within a predetermined time period, and to adjust the activity level of the tags based on the access frequency. The tag management engine is further configured to remove tags from the set of tags with an activity level that is less than a purge threshold.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine, a tagging engine, and a resource allocation engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to modify metadata for the audio file to include AI-defined tags. The resource allocation engine is configured to identify a storage location from among the plurality of storage devices based on tags associated with the audio file and send the audio file to the identified storage location.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine and a tagging engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to identify observed concepts within the audio file. The tagging engine is further configured to compare the observed concepts to the first set of concepts, to determine one or more observed concepts matches concepts linked with AI-defined tags, and to modify metadata for the audio file to include AI-defined tags.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine, a tagging engine, and a resource allocation engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to modify metadata for the audio file to include AI-defined tags. The resource allocation engine is configured to identify a storage location from among the plurality of storage devices based on tags associated with the audio file and send the audio file to the identified storage location.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine and a tag management engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tag management engine is configured to receive an audio file, identify tags linked with the audio file, to determine an access frequency for the audio file within a predetermined time period, and to adjust the activity level of the tags based on the access frequency. The tag management engine is further configured to remove tags from the set of tags with an activity level that is less than a purge threshold.

Abstract: Aspects of the disclosure relate to multicomputer systems and methods for data authentication and event execution using a blockchain approach. Any full node computing device in a network, including a data authentication and event execution computing platform, may receive data from one or more sources. The computing platform may verify the authenticity of at least one aspect of the received data. Once the authenticity of the data has been verified, the computing platform may generate a new block of a user's blockchain by cryptographically encrypting the received data, may add the new block to the user's blockchain, and may store the updated blockchain. The platform may then transmit an indication that the received data has been authenticated to the data source. In addition, the computing platform may generate a command configured to execute an action associated with the new block and may transmit the command to the data source.

Abstract: Aspects of the disclosure relate to multicomputer systems and methods for data authentication and event execution using a blockchain approach. Any full node computing device in a network, including a data authentication and event execution computing platform, may receive data from one or more sources. The computing platform may verify the authenticity of at least one aspect of the received data. Once the authenticity of the data has been verified, the computing platform may generate a new block of a user's blockchain by cryptographically encrypting the received data, may add the new block to the user's blockchain, and may store the updated blockchain. The platform may then transmit an indication that the received data has been authenticated to the data source. In addition, the computing platform may generate a command configured to execute an action associated with the new block and may transmit the command to the data source.

Abstract: Aspects of the disclosure relate to implementing and using a data processing system to allocate transactions to one or more linked user accounts. A computing platform having at least one processor, a memory, and a communication interface may read, from a blockchain, transaction information pertaining to a transaction between a user and a participant. The computing platform may identify the user and a plurality of linked user accounts, and then execute an algorithm for generating allocation information for allocating the transaction to one or more of the linked user accounts. The computing platform may establish, via the communication interface, a first connection with a user computing device and, while the first connection is established, transmit to the user computing device the allocation information which, when executed by the user computing device, causes a notification to be displayed on the user computing device.

Abstract: Aspects of the disclosure relate to multicomputer systems and methods for data authentication and event execution using a blockchain approach. Any full node computing device in a network, including a data authentication and event execution computing platform, may receive data from one or more sources. The computing platform may verify the authenticity of at least one aspect of the received data. Once the authenticity of the data has been verified, the computing platform may generate a new block of a user's blockchain by cryptographically encrypting the received data, may add the new block to the user's blockchain, and may store the updated blockchain. The platform may then transmit an indication that the received data has been authenticated to the data source. In addition, the computing platform may generate a command configured to execute an action associated with the new block and may transmit the command to the data source.