Formatting electronic messages using machine learning
Disclosed herein are examples of systems and methods for formatting electronic messages using machine learning. An electronic message can be obtained, and a processed message can be generated based at least in part on the electronic message. At least one attribute for the processed message can be determined. A formatting specification can be generated based at least in part on the at least one attribute. A reformatted message can be generated based at least in part on the formatting specification.
1. A system comprising:
at least one computing device comprising a processor and a memory; and
machine-readable instructions stored in the memory that, when executed by the processor, cause the at least one computing device to at least:
obtain an electronic message to be transmitted to a plurality of recipients including at least a first recipient and a second recipient;
generate a processed message based at least in part on the electronic message;
determine at least one attribute for the processed message;
generate a first formatting specification for reformatting text in a body of the electronic message for the first recipient based at least in part on a mapping of the at least one attribute to a formatting preference defined for the first recipient of the electronic message and a second formatting specification for reformatting text in a body of the electronic message for the second recipient based at least in part on a mapping of the at least one attribute to a formatting preference defined for the second recipient of the electronic message; and
generate a first reformatted message for the first recipient based at least in part on the first formatting specification and a second reformatted message for the second recipient based at least in part on the second formatting specification.
2. The system of claim 1 , wherein the at least one attribute comprises at least one of: a relationship between a sender of the electronic message and the recipient of the electronic message, a type of the electronic message, and a frequency of messages sent.
3. The system of claim 1 , wherein the machine-readable instructions that cause the at least one computing device to at least generate the processed message further cause the at least one computing device to at least:
identify a formatting element in the electronic message;
generate a token corresponding to the formatting element; and
generate the processed message based at least in part on the formatting element.
4. The system of claim 1 , wherein the reformatted message is generated using a sequence-to-sequence model.
5. The system of claim 4 , wherein the machine-readable instructions, when executed by the processor, further cause the at least one computing device to at least:
obtain a plurality of electronic messages;
generate a plurality of processed messages based at least in part on the plurality of electronic messages; and
train the sequence-to-sequence model using the plurality of processed messages.
6. A method for reformatting an electronic message, comprising:
obtaining an electronic message to be transmitted to a plurality of recipients including at least a first recipient and a second recipient;
generating a processed message based at least in part on the electronic message;
determining at least one attribute for the processed message;
generating a first formatting specification for reformatting text in a body of the electronic message for the first recipient based at least in part on a mapping of the at least one attribute to a formatting preference defined for the first recipient of the electronic message and a second formatting specification for reformatting text in a body of the electronic message for the second recipient based at least in part on a mapping of the at least one attribute to a formatting preference defined for the second recipient of the electronic message; and
generating a first reformatted message for the first recipient based at least in part on the first formatting specification and a second reformatted message for the second recipient based at least in part on the second formatting specification.
7. The method of claim 6 , wherein the at least one attribute comprises at least one of: a relationship between a sender of the electronic message and the recipient of the electronic message, a type of the electronic message, and a frequency of messages sent.
8. The method of claim 6 , wherein the formatting specification comprises a set of formatting rules corresponding to the at least one attribute.
9. The method of claim 6 , wherein generating the processed message based at least in part on the electronic message further comprises:
identifying a formatting element in the electronic message;
generating a token corresponding to the formatting element; and
generating the processed message based at least in part on the formatting element.
10. The method of claim 6 , wherein the reformatted message is generated using a sequence-to-sequence model.
11. The method of claim 10 , further comprising:
obtaining a plurality of electronic messages;
generating a plurality of processed messages based at least in part on the plurality of electronic messages; and
training the sequence-to-sequence model using the plurality of processed messages.
12. A non-transitory, computer-readable medium comprising machine-readable instructions that, when executed by a processor of at least computing device, cause the processor to at least:
obtain an electronic message to be transmitted to a plurality of recipients including at least a first recipient and a second recipient;
generate a processed message based at least in part on the electronic message;
determine at least one attribute for the processed message;
generate a first formatting specification for reformatting text in a body of the electronic message for the first recipient based at least in part on a mapping of the at least one attribute to a formatting preference defined for the first recipient of the electronic message and a second formatting specification for reformatting text in a body of the electronic message for the second recipient based at least in part on a mapping of the at least one attribute to a formatting preference defined for the second recipient of the electronic message; and
generate a first reformatted message for the first recipient based at least in part on the first formatting specification and a second reformatted message for the second recipient based at least in part on the second formatting specification.
13. The non-transitory, computer-readable medium of claim 12 , wherein the at least one attribute comprises at least one of: a relationship between a sender of the electronic message and the recipient of the electronic message, a type of the electronic message, and a frequency of messages sent.
14. The non-transitory, computer-readable medium of claim 12 , wherein the formatting specification comprises a set of formatting rules corresponding to the at least one attribute.
15. The non-transitory, computer-readable medium of claim 12 , wherein the machine-readable instructions that cause the processor to at least generate the processed message further cause the processor to at least:
identify a formatting element in the electronic message;
generate a token corresponding to the formatting element; and
generate the processed message based at least in part on the formatting element.
16. The non-transitory, computer-readable medium of claim 12 , wherein the reformatted message is generated using a sequence-to-sequence model, and the machine-readable instructions, when executed by the processor, further cause the processor to at least:
obtain a plurality of electronic messages;
generate a plurality of processed messages based at least in part on the plurality of electronic messages; and
train the sequence-to-sequence model using the plurality of processed messages.