I have a spreadsheet with thousands of records regarding support requests. Case number, Issue description, etc.
Our goal is to classify these records in many categories in order to assign them the right priority.
- Customer can't use pickup feature.
- Customer can't dial 911 or Long Distance numbers.
For item number 1, I have decided to use a category called Best Effort and for item 2, an Urgent category.
- Customer can't use pickup feature, BEST_EFFORT
- Customer can't dial 911 or Long Distance numbers, URGENT
I'm planning to setup a dictionary of words.
best_effort = ['pickup','record','conference'] urgent = ['system is down','911', 'can't dial emergency','call center is down']
My goal is to use TFIDF and then cosine similarity to find best match and category. Does it makes sense? Any better recommendation to classify this type of information?