Apparatuses and methods for classifying a user to a posting

1. An apparatus for using machine learning to classify a user to a posting, the apparatus comprising:

at least a processor; and

a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to:

acquire a plurality of user inputs from a user comprising:

receiving textual data;

receiving a plurality of identified documents;

analyzing one or more words extracted from the plurality of identified documents using a language processing module;

comparing the textual data to the one or more words; and

extracting the plurality of user inputs from the textual data as a function of the comparison;

acquire a plurality of posting inputs from a plurality of postings, wherein a posting input comprises at least a desired employee personality trait;

compare the plurality of user inputs to the plurality of posting inputs, wherein the plurality of user inputs are compared to the plurality of posting inputs utilizing a knowledge-based system, and wherein the knowledge-based system further comprises a knowledge base and an inference engine; and

classify the user to a posting category as a function of the comparison, wherein classifying the user to the posting category comprises:

training, iteratively a machine learning model using training data and a machine learning algorithm, wherein the training data includes the plurality of user and the plurality of posting inputs correlated with similarity scores; and

generating a similarity score using the trained machine learning model wherein the plurality of user inputs and the plurality of posting inputs are provided as an input to the trained machine learning model to output an updated similarity score;

output a plurality of job postings matching the posting category based on the updated similarity score;

rank the plurality of job postings as a function of the updated similarity score; classify the plurality of job postings to at least a category; and

output the classified ranked job postings in a color-coded pie chart.

2. The apparatus of claim 1 , wherein a user input is acquired from at least an experience record of a user.

3. The apparatus of claim 1 wherein a posting input further comprises at least a list of skill requirements.

4. The apparatus of claim 1 , wherein the plurality of postings are video records.

5. The apparatus of claim 1 , further comprising the language processing module to acquire the similarity score.

6. The apparatus of claim 1 , wherein a ranking of the plurality of postings is based on the similarity score.

7. The apparatus of claim 6 , wherein the ranking of the plurality of postings is configured using at least linear regression techniques.

8. The apparatus of claim 1 , wherein classifying the user to the posting category comprises a classifier algorithm wherein the algorithm output is a plurality of postings optimized for the user.

9. A method for using machine learning to classify a user to a posting, the method comprising:

acquiring, using a computing device, a plurality of user inputs from a user comprising:

receiving textual data;

receiving a plurality of identified documents;

analyzing one or more words extracted from the plurality of identified documents using a language processing module;

comparing the textual data to the one or more words; and

extracting the plurality of user inputs from the textual data as a function of the comparison;

acquiring, using the computing device, a plurality of posting inputs from a plurality of postings, wherein a posting input comprises at least a desired employee personality trait;

comparing, using the computing device, the plurality of user inputs to the plurality of posting inputs, wherein the plurality of user inputs are compared to the plurality of posting inputs utilizing a knowledge-based system, and wherein the knowledge-based system further comprises a knowledge base and an inference engine; and

classifying, using the computing device, the user to a posting category as a function of the comparison, wherein classifying the user to the posting category comprises:

training, iteratively a machine learning model using training data and a machine learning algorithm, wherein the training data includes the plurality of user and the plurality of posting inputs correlated with similarity scores; and

generating a similarity score using the trained machine learning model wherein the plurality of user inputs and the plurality of posting inputs are provided as an input to the trained machine learning model to output an updated similarity score;

outputting a plurality of job postings matching the posting category based on the updated similarity score;

ranking the plurality of job postings as a function of the updated similarity score;

classifying the plurality of job postings to at least a category; and

outputting the classified ranked job postings in a color-coded pie chart.

10. The method of claim 9 , wherein a user input is acquired from at least an experience record of a user.

11. The method of claim 9 wherein a posting input comprises at least a list of skill requirements.

12. The method of claim 9 , wherein the plurality of postings are video records.

13. The method of claim 9 , further comprising the language processing module to acquire the similarity score.

14. The method of claim 9 , wherein a ranking of the plurality of postings is based on the similarity score.

15. The method of claim 14 , wherein the ranking of the plurality of postings is configured using at least linear regression techniques.

16. The method of claim 9 , wherein classifying the user to the posting category comprises a classifier algorithm wherein the algorithm output is a plurality of postings optimized for the user.