The indexing process is typically performed:
Anonymous Quiz
9%
Only when a document is updated
0%
At query time(online)
9%
Both online and offline
82%
Offline,before any queries are received
The first step in the text preprocessing pipeline is:
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0%
Case folding
11%
Stemming
11%
Stopping
78%
Tokenization
Tokenization is the process of:
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9%
Removing common words
0%
Translating words into another language
55%
Splitting a text stream into individual tokens(words)
36%
Reducing words to their root form
A significant challenge in tokenizing text from social media (like Twitter) is:
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9%
The text is too long
0%
The text is in multiple languages
0%
There are no spaces between words
91%
Handling hashtags(#), mentions (@), and emoticons
The main reason for removing stop words is to:
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9%
Make the text easier to read
0%
Improve grammatical correctness
9%
Increase the number of relevant documents
82%
Reduce the size of the index and improve efficiency
For which type of query is stop word removal particularly problematic?
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0%
Queries with spelling errors
9%
Boolean AND queries
0%
Queries with very rare terms
91%
Phrase queries(e.g., to be or not to be)
What is the main goal of Information Retrieval (IR) systems?
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0%
Store structured data
91%
Find unstructured documents that satisfy the user’s need
0%
Compress data
9%
Translate texts
Which of these applications is an example of IR?
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17%
Searching emails
0%
Spam filtering
25%
Searching images or videos
58%
All of the above
What is the main difference between IR and databases?
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82%
IR deals with free text, while databases handle structured data
9%
Databases are slower
0%
IR is always more accurate
9%
No difference
In IR, which component represents the user’s need?
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20%
Documents
40%
Query
0%
Index
40%
Search engine
What are the main challenges in IR?
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73%
Efficiency and effectiveness
9%
Algorithm design
9%
Text size only
9%
Language accuracy
How is a document defined in IR systems?
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8%
Only a structured element
92%
An element with a unique identifier; it can be text, image, or video
0%
A small database
0%
A fixed text paragraph
Which of these can be considered a query in IR?
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15%
Free text
15%
Image as a search input
23%
Musical tune for song search
46%
All of the above
What does “Relevance” mean in IR?
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43%
Exact match between query text and document
50%
How well the document satisfies the user’s need
7%
Document size
0%
Indexing speed
Which is true about Bag of Words?
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69%
Treats a document as a set of words without order
23%
Preserves word order
8%
Only for noscripts
0%
Only used in databases
In Boolean model, which operation expands results?
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8%
AND
15%
OR
0%
NOT
77%
All of the above
Query: AI AND ML returns:
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18%
Documents containing either
64%
Documents containing both
9%
Documents without AI
9%
Documents without ML
Query: cloud NOT storage returns:
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17%
All documents
50%
Documents containing cloud only, not storage
8%
Documents containing storage only
25%
Nothing
How does the Boolean model partition the set?
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67%
Matching / non-matching documents
22%
Important / unimportant documents
0%
Recent / old documents
11%
Short / long documents
What does Exact-Match Retrieval mean?
Anonymous Quiz
67%
Retrieve documents that fully satisfy the query
11%
Retrieve similar documents
11%
Retrieve related documents
11%
No meaning