Automatic equation transformation from text

1. A method for automatic equation transformation from text, the method comprising:

receiving a text document;

identifying a mathematical formula expressed in the received text document;

removing a plurality of superfluous language from the received text document based on the identified mathematical formula;

transforming the identified mathematical formula into a symbolic representation based on a trained model;

utilizing a natural language processing technique to generate a tree-like structure using an identified plurality of mathematical equation language,

wherein the tree-like structure is generated using an equation dependency parser, an input stack, a processed stack,

wherein a neural network with one or more hidden layers is implemented with the equation dependency parser,

wherein an input layer of the neural network is represented by a semantic embedding variable, a named-entity recognition variable, a surrounding word variable, and a label embedding vector; and

wherein an output layer of the neural network is represented using a softmax function; and

outputting the symbolic representation.

2. The method of claim 1 , wherein the received text document is a variable length determined by a user.

3. The method of claim 1 , wherein identifying the mathematical formula expressed in the received text document further comprises:

identifying a plurality of keywords by parsing through a plurality of text associated with the received text document; and

comparing the identified plurality of keywords to a database of known mathematical symbols.

4. The method of claim 3 , wherein identifying the plurality of keywords by parsing through the plurality of text associated with the received text document comprises utilizing an indexing technique to search the received text document.

5. The method of claim 1 , wherein removing the plurality of superfluous language from the received text document further comprises:

performing a syntactic analysis of the received text document; and

removing a plurality of language from the received text document that is not part of the generated tree-like structure.

6. The method of claim 1 , wherein the output mathematical equation is a downloadable text document.

7. A computer system for automatic equation transformation from text, comprising:

one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:

receiving a text document;

identifying a mathematical formula expressed in the received text document;

removing a plurality of superfluous language from the received text document based on the identified mathematical formula;

transforming the identified mathematical formula into a symbolic representation based on a trained model;

utilizing a natural language processing technique to generate a tree-like structure using an identified plurality of mathematical equation language,

wherein the tree-like structure is generated using an equation dependency parser, an input stack, a processed stack,

wherein a neural network with one or more hidden layers is implemented with the equation dependency parser,

wherein an input layer of the neural network is represented by a semantic embedding variable, a named-entity recognition variable, a surrounding word variable, and a label embedding vector; and

wherein an output layer of the neural network is represented using a softmax function; and

outputting the symbolic representation.

8. The computer system of claim 7 , wherein the received text document is a variable length determined by a user.

9. The computer system of claim 7 , wherein identifying the mathematical formula expressed in the received text document further comprises:

identifying a plurality of keywords by parsing through a plurality of text associated with the received text document; and

comparing the identified plurality of keywords to a database of known mathematical symbols.

10. The computer system of claim 9 , wherein identifying the plurality of keywords by parsing through the plurality of text associated with the received text document comprises utilizing an indexing technique to search the received text document.

11. The computer system of claim 7 , wherein removing the plurality of superfluous language from the received text document further comprises:

performing a syntactic analysis of the received text document; and

removing a plurality of language from the received text document that is not part of the generated tree-like structure.

12. The computer system of claim 7 , wherein the output mathematical equation is a downloadable text document.

13. A computer program product for automatic equation transformation from text, comprising:

one or more computer-readable storage media and program instructions stored on at least one of the one or more tangible storage media, the program instructions executable by a processor to cause the processor to perform a method comprising:

receiving a text document;

identifying a mathematical formula expressed in the received text document;

removing a plurality of superfluous language from the received text document based on the identified mathematical formula;

transforming the identified mathematical formula into a symbolic representation based on a trained model;

utilizing a natural language processing technique to generate a tree-like structure using an identified plurality of mathematical equation language,

wherein the tree-like structure is generated using an equation dependency parser, an input stack, a processed stack,

wherein a neural network with one or more hidden layers is implemented with the equation dependency parser,

wherein an input layer of the neural network is represented by a semantic embedding variable, a named-entity recognition variable, a surrounding word variable, and a label embedding vector; and

wherein an output layer of the neural network is represented using a softmax function; and

outputting the symbolic representation.

14. The computer program product of claim 13 , wherein the received text document is a variable length determined by a user.

15. The computer program product of claim 13 , wherein identifying the mathematical formula expressed in the received text document further comprises:

identifying a plurality of keywords by parsing through a plurality of text associated with the received text document; and

comparing the identified plurality of keywords to a database of known mathematical symbols.

16. The computer program product of claim 15 , wherein identifying the plurality of keywords by parsing through the plurality of text associated with the received text document comprises utilizing an indexing technique to search the received text document.

17. The computer program product of claim 13 , wherein removing the plurality of superfluous language from the received text document further comprises:

performing a syntactic analysis of the received text document; and

removing a plurality of language from the received text document that is not part of the generated tree-like structure.