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Microsoft AI-900 Exam - Topic 5 Question 55 Discussion

Actual exam question for Microsoft's AI-900 exam
Question #: 55
Topic #: 5
[All AI-900 Questions]

You are building a chatbot that will use natural language processing (NLP) to perform the following actions based on the text input of a user:

* Accept customer orders.

* Retrieve support documents.

* Retrieve order status updates.

Which type of NLP should you use?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Donte at Dec 08, 2023, 08:23 AM

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Laurel
6 months ago
Not sure if language modeling is the best choice...
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Charlena
6 months ago
Wait, can translation even be relevant here?
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Janet
6 months ago
Named entity recognition could help with tracking orders.
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Jovita
7 months ago
Definitely not sentiment analysis for orders!
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Howard
7 months ago
I think language modeling is the way to go for this.
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Norah
7 months ago
I feel like translation isn't the right choice here either. We need something that can handle specific tasks like retrieving info, so maybe language modeling?
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Cornell
7 months ago
I'm a bit confused about which option fits best. Sentiment analysis seems more about emotions, not really about processing orders.
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Argelia
7 months ago
I remember practicing with a question about chatbots, and I think named entity recognition could be relevant for identifying specific orders or documents.
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Berry
8 months ago
I think we might need to use language modeling since it helps understand user input better, but I'm not entirely sure.
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Aliza
8 months ago
Sentiment analysis seems like it could be useful for the customer orders part, but I'm not sure it covers all the other requirements. I'll have to weigh the options and try to determine the most comprehensive solution.
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Mitsue
8 months ago
Okay, let's see. The chatbot needs to understand and respond to user input, so I'm thinking language modeling might be the way to go. That would allow the chatbot to generate relevant responses based on the context.
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Mendy
8 months ago
Hmm, I'm a bit unsure about this one. The question mentions natural language processing, but it's not clear which NLP technique would be best for the given requirements. I'll have to think this through carefully.
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Kanisha
8 months ago
This seems like a straightforward question. I think I'll go with named entity recognition since the chatbot needs to extract specific information like customer orders, support documents, and order status updates.
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Aracelis
8 months ago
Okay, let me review the options again. The geographic concentration of labor around Bangkok is definitely a labor market factor, as is demand for labor. Types of remuneration sought also seems relevant. I think I've got this!
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Emily
8 months ago
Alright, let me think this through step-by-step. The INVEST data set has 10 observations, but the question is asking about the FORCAST data set. So I'll need to consider how the program might be creating or modifying that data set. Time to put on my problem-solving hat!
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Felicitas
8 months ago
Option D sounds like a good idea, with department managers reviewing user access periodically. That way, any issues can be caught and addressed in a timely manner.
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Gregg
8 months ago
If my memory serves right, the couple with a $10 million net worth looks like a solid answer. High-net-worth often focuses on net investments.
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Susy
1 year ago
I'm going with named entity recognition. It's the clear choice to extract the critical details needed to process orders, look up support docs, and provide status updates. Anything else would be like trying to build a house with a screwdriver.
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Winfred
11 months ago
Yes, named entity recognition is the way to go for processing orders, retrieving documents, and getting status updates.
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Fernanda
11 months ago
Absolutely, named entity recognition is essential for extracting important information from text inputs.
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Gracia
11 months ago
I agree, named entity recognition is definitely the best choice for this task.
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Mitsue
11 months ago
D) named entity recognition
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Caren
11 months ago
C) language modeling
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Shannon
12 months ago
B) translation
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Rene
12 months ago
A) sentiment analysis
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Bernardine
1 year ago
Translation? Really? Unless your customers are from another planet, I don't see how that would be helpful here. Let's keep it grounded in Earth language, shall we?
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Kanisha
12 months ago
D) named entity recognition
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Osvaldo
1 year ago
C) language modeling
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Theron
1 year ago
A) sentiment analysis
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Becky
1 year ago
Sentiment analysis could be interesting, but it doesn't seem directly relevant to the core functionality the chatbot needs. I'd save that for a later enhancement.
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Rosina
1 year ago
Language modeling could be useful for understanding the overall context and intent behind the user's input. But I'm not sure it would be enough to handle all the specific actions the chatbot needs to perform.
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Cherelle
1 year ago
D) named entity recognition
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Larae
1 year ago
A) sentiment analysis
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Pearly
1 year ago
D) named entity recognition
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Kristeen
1 year ago
A) sentiment analysis
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Roselle
1 year ago
I think named entity recognition is the way to go for this chatbot. It can help identify key pieces of information like customer names, order numbers, and product details.
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Martha
1 year ago
I'm not sure about named entity recognition, I think sentiment analysis could also be useful to understand customer feedback.
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Dean
1 year ago
I agree with Buck, named entity recognition would be the best choice to extract specific information like customer orders and order status updates.
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Buck
1 year ago
I think we should use named entity recognition for this.
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