1
$\begingroup$

I'm trying to solve a 'negation-like' classification problem, where I need to classify whether a certain word within the context has negative or positive label.

For example, how to identify whether a keyword has been prescribed or only mentioned:

['Aspirin has been prescribed to a patients'] -> {[('key_word': 'aspirin', 'prescribed': TRUE)]}

['If symptoms continue, the patient should consider taking Omeprazol'] -> {[('key_word': 'omeprazol', 'prescribed': FALSE)]}

[‘The plan is for him to commence 25mg of Trazodone as soon as he gets better.’] -> {[('key_word': 'trazodone ', 'prescribed': FALSE)]}

['her current meds are: sertraline 200 mg and olanzapine 5 mg'] -> {[('key_word': 'sertraline', 'prescribed': TRUE), ('key_word': 'olanzapine', 'prescribed': TRUE)]}

['if she continues to be depressed, then she needs to be started on Risperidone'] -> {[('key_word': 'risperidone', 'prescribed': FALSE)]}

I have a training data set for this task, but it is not clear how to formulate the classification problem. It is similar to sentiment classification problem, but here instead of predicting a label of the entire sentence, I need to predict a label of a certain keyword based on the context.

Any ideas?

$\endgroup$
3
  • 1
    $\begingroup$ You could try 3-grams and 4-grams TFIDF and then a Multinomial Naive Bayes Classifier. Is the key_word a part of the label? $\endgroup$
    – Danny
    Feb 11, 2019 at 15:43
  • $\begingroup$ @Danny, thanks. No, I provide the key_word to specify where the algorithm should be looking at (it should attend to my key_word and make decision about it). $\endgroup$ Feb 11, 2019 at 16:41
  • 1
    $\begingroup$ Just make sure you remove the stop words and stem the words as well. I am afraid I still don't understand how the key_word is used. But, this approach should give you good enough results to visualise clusters and then see how can you improve your approach. $\endgroup$
    – Danny
    Feb 11, 2019 at 16:45

0

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Browse other questions tagged or ask your own question.