Electronic message composition support method and apparatus

A method comprising:

• obtaining, by a computing device, training data comprising a number of training examples, each training example comprising a set of features and having a corresponding label indicating whether or not the example is a positive example of a condition;
• training, by the computing device and using a machine learning algorithm, a linter using the training data, the linter for use in detecting the condition in connection with electronic message input, of a user, the training comprising training the linter to recognize whether or not a feature, of the set of features, is a predictive feature of the condition;
• generating, by the computing device, feature set input using the electronic message input, of the user, the feature set input comprising the set of features generated using the electronic message input;
• making a determination, by the computing device and using the linter, whether or not the condition exists with the electronic message input, the determining comprising:
• providing the feature set input as input to the linter;
• and
• receiving output, from the linter, the output being used to make the determination;
• generating, by the computing device, feedback indicative of the condition in accordance with the determination;
• and
• displaying, via the computing device, the feedback to the user.

A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a processor associated with a computing device perform a method comprising:

• obtaining training data comprising a number of training examples, each training example comprising a set of features and having a corresponding label indicating whether or not the example is a positive example of a condition;
• training, using a machine learning algorithm, a linter using the training data, the linter for use in detecting the condition in connection with electronic message input, of a user, the training comprising training the linter to recognize whether or not a feature, of the set of features, is a predictive feature of the condition;
• generating feature set input using the electronic message input, of the user, the feature set input comprising the set of features generated using the electronic message input;
• making a determination, using the linter, whether or not the condition exists with the electronic message input, the determining comprising:
• providing the feature set input as input to the linter;
• and
• receiving output, from the linter, the output being used to make the determination;
• generating feedback indicative of the condition in accordance with the determination;
• and
• displaying the feedback to the user.

A computing device comprising:

• a processor;
• a non-transitory storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising:
• obtaining logic executed by the processor for obtaining training data comprising a number of training examples, each training example comprising a set of features and having a corresponding label indicating whether or not the example is a positive example of a condition;
• training logic executed by the processor for training, using a machine learning algorithm, a linter using the training data, the linter for use in detecting the condition in connection with electronic message input, of a user, the training comprising training the linter to recognize whether or not a feature, of the set of features, is a predictive feature of the condition;
• generating logic executed by the processor for generating feature set input using the electronic message input, of the user, the feature set input comprising the set of features generated using the electronic message input;
• making logic executed by the processor for making a determination, using the linter, whether or not the condition exists with the electronic message input, the determining comprising:
• providing the feature set input as input to the linter;
• and
• receiving output, from the linter, the output being used to make the determination;
• generating logic executed by the processor for generating feedback indicative of the condition in accordance with the determination;
• and
• displaying logic executed by the processor for displaying the feedback to the user.