What is the primary purpose of using fuzzy matching in search engines?
Elasticsearch 7 and Elastic Stack - In Depth and Hands On! - Fuzzy Queries

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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
To improve the accuracy of search results
To increase the speed of search queries
To reduce the size of the search index
To handle typos and misspellings in user input
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a type of error considered in Levenshtein distance?
Substitution
Repetition
Insertion
Deletion
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
If a user misspells 'interstellar' as 'intersteller', what type of error is this?
Substitution
Insertion
Deletion
Transposition
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the 'auto' setting for fuzziness affect short strings?
It only applies to strings longer than five characters
It increases the fuzziness tolerance for all strings
It does not tolerate any fuzziness for one or two character strings
It allows more errors for short strings
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What happens when a fuzziness level of 1 is specified for a search query?
Matches with up to two errors are allowed
All possible matches are returned
Only exact matches are returned
Matches with one error are allowed
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the practical demonstration, what was the result of searching for 'wars' with a Z using a fuzziness of 1?
No results were returned
Only exact matches were returned
Results including 'Star Wars' were returned
An error occurred in the search
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the effect of increasing the fuzziness level in a search query?
It decreases the number of potential matches
It allows for more errors in the search term
It speeds up the search process
It restricts the search to exact matches only
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