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Huawei Exam H13-321 Topic 1 Question 84 Discussion

Actual exam question for Huawei's H13-321 exam
Question #: 84
Topic #: 1
[All H13-321 Questions]

The bag-of-words model is the earliest text vectorization method with words as the basic processing unit. Which of the following options is not the bag of words model.

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Suggested Answer: C

Contribute your Thoughts:

Torie
5 months ago
Hmm, that makes sense. I can see how option A) makes more sense as not being part of the bag of words model.
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Naomi
6 months ago
I agree with user 3, option A) Based on the distribution assumption does not align with the bag of words model.
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Virgie
6 months ago
I believe option A) Based on the distribution assumption is not part of the bag of words model.
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Sharee
6 months ago
I disagree, option B) There is a semantic gap is actually a characteristic of the bag of words model.
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Torie
6 months ago
I think option B) There is a semantic gap is not the bag of words model.
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Franchesca
6 months ago
Yes, but it's actually option D) Order information cannot be retained that is not characteristic of the bag of words model.
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Nickole
6 months ago
But doesn't the bag of words model suffer from dimensional disaster?
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Kattie
6 months ago
I'm leaning towards option C) Dimensional disaster not being the bag of words model.
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Franchesca
6 months ago
I disagree, I believe option B) There is a semantic gap is not the bag of words model.
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Nickole
7 months ago
I think option A) Based on the distribution assumption is not the bag of words model.
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Ozell
8 months ago
You know, I'm starting to think option D, 'order information cannot be retained', might also be a valid answer. The bag-of-words model completely ignores the order of words, which can be important for understanding context and meaning. That seems like a pretty significant shortcoming to me.
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Temeka
8 months ago
Haha, 'dimensional disaster'? What a great term! I'm definitely going to remember that one. But yeah, I think I'm leaning towards option B as the answer. The bag-of-words model is all about surface-level word frequencies, so the semantic gap is a pretty fundamental limitation.
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Beatriz
8 months ago
Ooh, good point, Trina. The 'dimensional disaster' is a well-known issue with the bag-of-words model. Though I suppose you could argue that the lack of semantic awareness (option B) is also a pretty big limitation. Tough choice!
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Trina
8 months ago
Hmm, I'm not so sure. Option C, 'dimensional disaster', could also be a valid answer. The bag-of-words model can create really high-dimensional feature vectors, which can be computationally expensive and lead to overfitting. That seems like a more relevant drawback to me.
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Moira
8 months ago
Yeah, I agree with Leana. The bag-of-words model is all about counting word frequencies without any consideration for meaning or context. So option B definitely doesn't apply. I'm leaning towards that as the answer.
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Lorrie
7 months ago
Then option B, There is a semantic gap, is not the bag of words model.
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Louisa
7 months ago
I agree, the bag-of-words model doesn't consider semantics.
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Jordan
7 months ago
I think option B is correct.
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Leana
8 months ago
The bag-of-words model is a pretty basic text vectorization technique, so I'm not surprised it's on the exam. I think option B, 'there is a semantic gap', is not a characteristic of the bag-of-words model. The bag-of-words model doesn't really capture semantic relationships between words, so there's no semantic gap to worry about.
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