I am new to NLP, I have a bunch of raw data that is not tagged at all of medical questions, I need to extract from them what are the health issues stated in those texts.
I was thinking I need to create two custom POS tags for NER:
-the location on the body
-the problem itself
So if someone asked 'my head hurts' it would understand that the location is the head and the problem is that it hurts, but if someone asked 'my skin is red around my abdomen' it would understand that the location is the abdomen and the problem is that the skin is red.
After I extract this data I need to recommend medical articles based on what that user asked.
I have some questions:
1.Am I on the right path?
2.How would you implement it?
3.Do I need a custom pos tag for the location and the health issue or can it be done easier? How would you extract those informations?
4.I guess I have to manually tag questions right?
5.What framework would you use?
6.To create a recommender system I need to extract the same informations from medical articles?
7.How would you create a recommender system?
As I said, I am new to NLP and I didn't decide on the framework yet but the questions are not in english, I have found however on github a WordNet clone and a Named Entity Corpus for my language, so please keep in mind when recommending frameworks.