Systems and methods for automatic identification and recommendation of techniques and experts

A system comprising:

• one or more processors;
• and
• one or more memory devices storing computer code that when executed by the one or more processors causes the system to:
• receive a first text indicative of a first coding script;
• responsive to identifying a first coding technique from the first text, query a database, using a first search query comprising the identity of the first coding technique, to determine if the database recognizes the first coding technique, the database storing coding technique classifications and language drafted by a plurality of authors;
• responsive to receiving an indication that the database does not recognize the first coding technique, create a first model of the first text comprising one or more words associated with the first coding technique, wherein creating the first model further comprises parsing the first search query for language associated with the first coding technique and creating a first bag-of-words model of the first text comprising one or more words associated with the first coding technique;
• send a first update to the database comprising the first model, a name for each of one or more respective authors of the first coding technique, and an updated respective number of models used by each author of the first coding technique;
• determine if the first coding script comprises additional techniques by comparing the first text to a library of coding technique terms;
• and
• responsive to identifying a second coding technique based on the library of coding techniques, send a second update to the database comprising data indicative of the second coding technique.

A method comprising:

• receiving, at a first computing device, a request to identify a coding expert, the request comprising first text of a draft implementation of a first machine-learning algorithm from a user that is drafting the draft implementation of the first machine-learning algorithm;
• querying a database to determine if the database comprises a first machine-learning coding technique corresponding to the first machine-learning algorithm, the database storing data indicative of machine-learning functions and languages corresponding to a plurality of authors;
• responsive to receiving an indication that the database does not have the first machine-learning coding technique, updating the database by:
• analyzing the first text using one or more natural language processing techniques;
• generating a model of the first text comprising one or more words associated with machine-learning algorithms;
• updating the database to include data indicative of the first text and a name of each of one or more authors of the first text;
• determining if the draft comprises additional machine-learning coding techniques by comparing the first text to a library of machine-learning techniques terms;
• and
• responsive to identifying a second coding technique based on the library of machine-learning coding techniques, updating the database to include data indicative of the second machine-learning coding technique.