BlackFriday 2024! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Pegasystems Exam PEGACPDS88V1 Topic 7 Question 22 Discussion

Actual exam question for Pegasystems's PEGACPDS88V1 exam
Question #: 22
Topic #: 7
[All PEGACPDS88V1 Questions]

To optimize their customer interactions, U+ Bank routes all emails that are complaints to a specialized department. To identify emails that voice a complaint, the text prediction uses___________

Show Suggested Answer Hide Answer
Suggested Answer: A

To identify emails that voice a complaint, the text prediction usesan entity extraction model.


Contribute your Thoughts:

William
1 months ago
I'm going with option C. A language model can probably do a better job of understanding the nuance and context in those complaints. Plus, it adds a touch of linguistic flair to the whole process.
upvoted 0 times
Denny
3 days ago
I'm leaning towards option B, a topic model, to categorize the complaints effectively.
upvoted 0 times
...
Shawnee
5 days ago
I agree with option D, a sentiment model, as it can detect the emotions behind the complaints.
upvoted 0 times
...
Nieves
28 days ago
I think option A, an entity extraction model, would be more accurate in identifying complaints.
upvoted 0 times
...
...
Shawn
2 months ago
Hmm, that's interesting. Can you explain why you think it's a sentiment model?
upvoted 0 times
...
Stefany
2 months ago
The sentiment model seems like the obvious choice here. I mean, who doesn't love a good old-fashioned emotional roller coaster when dealing with customer complaints?
upvoted 0 times
Nieves
7 days ago
D) a sentiment model
upvoted 0 times
...
Staci
8 days ago
C) a language model
upvoted 0 times
...
Demetra
11 days ago
B) a topic model
upvoted 0 times
...
Joesph
22 days ago
A) An entity extraction model
upvoted 0 times
...
...
Jerry
2 months ago
I disagree, I believe the answer is D) a sentiment model.
upvoted 0 times
...
Shawn
2 months ago
I think the answer is A) An entity extraction model.
upvoted 0 times
...

Save Cancel