| CPC G06F 16/383 (2019.01) [G06F 16/31 (2019.01); G06F 16/35 (2019.01); G06F 40/284 (2020.01)] | 20 Claims |
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1. An apparatus for note data analysis for unmet need identification, solution distillation and data structure generation, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:
receive a plurality of sets of note data, wherein the plurality of sets of note data comprises a variety of information related to a plurality of subjects generated by a plurality of users;
determine a plurality of operational language elements from the plurality of sets of note data, wherein the plurality of operational language elements comprises an unmet need language element and wherein determining the plurality of operational language elements comprises:
converting the plurality of sets of note data into a plurality of vectors in order to reduce a dimensionality of the plurality of sets of note data;
extracting, the plurality of operational language elements by identifying a degree of vector similarity between at least one vector within the plurality of vectors and a vector representing another language element;
identifying, using a large language model, an element connection within each of the plurality of operational language elements; and
identifying the unmet need language element as a function of the element connection;
generate an element control datum as a function of the unmet need language element of the plurality of operational language elements;
classify the plurality of operational language elements into one or more element groups;
generate a note data structure as a function of the one or more element groups and the element control datum; and
display the note data structure using a graphical user interface.
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11. A method for note data analysis for unmet need identification, solution distillation and data structure generation, the method comprising:
receiving, using at least a processor, a plurality of sets of note data, wherein the plurality of sets of note data comprises a variety of information related to a plurality of subjects generated by a plurality of users;
determining, using the at least a processor, a plurality of operational language elements from the plurality of sets of note data, wherein the plurality of operational language elements comprises an unmet need language element and wherein determining the plurality of operational language elements comprises:
converting the plurality of sets of note data into a plurality of vectors in order to reduce a dimensionality of the plurality of sets of note data;
extracting, the plurality of operational language elements by identifying a degree of vector similarity between at least one vector within the plurality of vectors and a vector representing another language element;
identifying, using a large language model, an element connection within each of the plurality of operational language elements; and
identifying the unmet need language element as a function of the element connection;
generating, using the at least a processor, an element control datum as a function of the unmet need language element of the plurality of operational language elements;
classifying, using the at least a processor, the plurality of operational language elements into one or more element groups;
generating, using the at least a processor, a note data structure as a function of the one or more element groups and the element control datum; and
displaying, using the at least a processor, the note data structure using a graphical user interface.
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