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CompTIA DY0-001 Exam - Topic 2 Question 6 Discussion

Which of the following measures would a data scientist most likely use to calculate the similarity of two text strings?
B) Edit distance
A) Word cloud
C) String indexing
D) k-nearest neighbors

CompTIA DY0-001 Exam - Topic 2 Question 6 Discussion

Actual exam question for CompTIA's DY0-001 exam
Question #: 6
Topic #: 2
[All DY0-001 Questions]

Which of the following measures would a data scientist most likely use to calculate the similarity of two text strings?

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Suggested Answer: B

Edit distance quantifies how many single-character insertions, deletions, or substitutions are needed to transform one string into another, making it a direct measure of their similarity.


by Judy at Jun 10, 2025, 05:45 PM

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Heidy
9 months ago
I thought word clouds were just for visualization, not similarity.
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Sang
9 months ago
Wait, isn't k-nearest neighbors more about classification?
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Lili
9 months ago
String indexing? That's not really a similarity measure, right?
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Flo
10 months ago
I totally agree, edit distance is super useful!
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Serita
10 months ago
Edit distance is a common method for text similarity!
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Dalene
10 months ago
String indexing sounds familiar, but I can't recall how it relates to measuring similarity. Edit distance feels more relevant to me.
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Bok
10 months ago
Word clouds seem more about visualization, so I doubt that's the answer. I feel like I've seen a question like this before.
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Rolf
11 months ago
I'm not entirely sure, but I remember something about k-nearest neighbors being used for classification rather than similarity directly.
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Jade
11 months ago
I think edit distance might be the right choice since it measures how many edits are needed to transform one string into another.
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Margurite
11 months ago
I'm a bit confused by this question. I know there are techniques like cosine similarity and Jaccard similarity that can be used for text, but I'm not sure if those are considered "measures" in the way the question is asking. I'll have to review my notes on text processing methods.
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Ilona
11 months ago
Okay, let me see. Word cloud is used for visualizing text, not measuring similarity. String indexing is more about storing and retrieving text, not comparing it. k-nearest neighbors is a machine learning technique, not a direct text similarity measure. That leaves edit distance as the best option.
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Kenda
11 months ago
Hmm, I'm not sure about this one. I know there are different ways to compare text, but I'm not familiar with all the options listed here. I'll have to think it through carefully.
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Carri
11 months ago
This seems like a straightforward question. I'm pretty confident the answer is B - edit distance. That's a common way to measure text similarity.
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