College admissions and career mentorship platform
The present disclosure provides a method, which may comprise obtaining a plurality of essay prompts, processing each essay prompt of said plurality of essay prompts using a natural language processing (NLP) algorithm to extract at least one feature from said each essay prompt and, using said at least one feature from said each essay prompt, generating two or more subsets of said plurality of essay prompts, wherein an essay prompt in a subset satisfies a measure of similarity with respect to each other essay prompt in said subset such that a single essay can be responsive to each essay prompt in said subset.
1. A method, comprising:
(a) obtaining a plurality of essay prompts;
(b) processing each essay prompt of said plurality of essay prompts using a natural language processing (NLP) algorithm to extract at least one feature from said each essay prompt;
(c) using said at least one feature from said each essay prompt, generating two or more subsets of said plurality of essay prompts, wherein an essay prompt in a subset satisfies a measure of similarity with respect to each other essay prompt in said subset such that a single essay can be responsive to each essay prompt in said subset; and
(d) providing an output comprising a report comprising said two or more subsets of said plurality of essay prompts.
2. The method of claim 1 , further comprising recommending a theme or topic for said single essay.
3. The method of claim 1 , wherein a quantity of said two or more subsets is minimized.
4. The method of claim 1 , wherein said natural language processing algorithm is a machine learning algorithm.
5. The method of claim 1 , wherein generating said two or more subsets of said plurality of essay prompts comprises processing said at least one feature from said each essay prompt using a clustering algorithm.
6. The method of claim 5 , wherein said clustering algorithm comprises a hierarchical clustering algorithm.
7. The method of claim 5 , wherein said clustering algorithm comprises a centroid-based clustering algorithm.
8. The method of claim 5 , wherein said clustering algorithm comprises a distribution-based clustering algorithm.
9. The method of claim 1 , wherein said obtaining in (a) comprises obtaining at least a portion of said plurality of essay prompts from at least one website.
10. The method of claim 1 , wherein said report is provided to a user.
11. The method of claim 1 , wherein said one or more features comprise one or more of a subject of an essay prompt, a call of an essay prompt, a category of an essay prompt, a topic of an essay prompt, and an allowed length of an essay.
12. The method of claim 1 , wherein said one or more features comprise one or more quantitative features.
13. The method of claim 1 , wherein said NLP algorithm comprises a rules-based algorithm, a statistical algorithm, a machine learning algorithm, a semantic analysis algorithm, or any combination thereof.
14. The method of claim 13 , wherein said NLP algorithm comprises a machine learning algorithm.
15. The method of claim 1 , further comprising providing a recommendation of an essay that is responsive to each essay prompt of a subset of said two or more subsets of said plurality of essay prompts.
16. The method of claim 1 , wherein said at least one feature comprises at least 5 features.
17. The method of claim 1 , wherein said user provides said plurality of essay prompts.