Information Retrieval Quizzes for Computer Science Students

Question 1

In pharmaceutical research, which of these is NOT a commonly used information retrieval model?

Accepted Answer

Knowledge graph model

Answer

Vector space model

Answer

Probabilistic model

Question 2

In Information Retrieval systems, which of these is NOT a commonly used evaluation metric?

Accepted Answer

Root Mean Squared Error

Answer

Precision

Answer

Recall

Answer

F-measure

Question 3

In the Vector Space Model, how is the relevance of a document to a query calculated?

Accepted Answer

Computing the cosine similarity between the document vector and the query vector

Answer

Counting the number of matching terms between the document and the query

Answer

Evaluating the inverse document frequency of terms within the document

Question 4

Which of the following is NOT a fundamental component of an information retrieval system?

Accepted Answer

Knowledge graph

Answer

Query processor

Answer

Indexer

Answer

Ranking mechanism

Question 5

What is the primary purpose of tokenization in information retrieval?

Accepted Answer

To identify individual words or terms in a document

Answer

To remove stop words from a document

Answer

To determine the frequency of terms in a document

Answer

To identify relevant documents for a given query

Question 6

Which ranking model is commonly associated with the vector space model?

Accepted Answer

TF-IDF model

Answer

Boolean model

Answer

Language model

Answer

Probabilistic model

Question 7

What is the primary purpose of the term frequency-inverse document frequency (TF-IDF) score?

Accepted Answer

To rank documents based on their relevance to a given query

Answer

To measure the frequency of a term within a single document

Answer

To identify duplicate documents in a dataset

Answer

To optimize the performance of search engine algorithms

Question 8

What is the primary purpose of a document index?

Accepted Answer

To provide a concise representation of document content for efficient retrieval.

Answer

To store the full text of every document for direct retrieval.

Answer

To maintain a history of user search queries for performance optimization.

Answer

To generate relevancy scores for ranking documents.

Question 9

Which ranking algorithm considers the number of other documents citing a particular document?

Accepted Answer

PageRank

Answer

TF-IDF

Answer

BM25

Answer

Vector Space Model

Question 10

What is the role of stop words in information retrieval?

Accepted Answer

They are removed from queries and documents to improve retrieval accuracy.

Answer

They are assigned higher weights to emphasize their importance.

Answer

They are used to expand queries by including synonyms and related terms.

Answer

They are essential for maintaining the semantic structure of text data.

Question 11

Which of the following is a characteristic of a Boolean model in information retrieval?

Accepted Answer

It uses logical operators to combine query terms.

Answer

It retrieves documents based on the frequency of query terms.

Answer

It assigns weights to query terms to calculate document relevance.

Answer

It considers the proximity of query terms within a document.

Question 12

What is a key advantage of using a vector space model in information retrieval?

Accepted Answer

It allows for partial matching of query terms with document terms.

Answer

It is computationally efficient, enabling large-scale retrieval systems.

Answer

It captures the semantic relationships between terms in a document.

Answer

It provides a compact representation of documents for indexing and searching.

Question 13

In the context of Probabilistic Retrieval Models, which of the following is NOT a probability ranking function?

Accepted Answer

BM25

Answer

Okapi BM25

Answer

Pivoted Length Normalization

Answer

Language Model

Question 14

Which of the following is NOT a crucial stage in the information retrieval process?

Accepted Answer

Data storage

Answer

Relevance ranking

Answer

Document retrieval

Answer

Query processing

Question 15

In information retrieval, what is the primary purpose of tokenization?

Accepted Answer

To decompose text documents into individual words or terms

Answer

To eliminate stop words from a query

Answer

To assign weights to terms in a document

Question 16

Which of the following relevance ranking algorithms is grounded in the vector space model?

Accepted Answer

Cosine similarity

Answer

Neural ranking models

Answer

Okapi BM25

Answer

Language modeling

Question 17

In the context of information retrieval, what is the definition of a stop word?

Accepted Answer

A commonly used word that is excluded during the indexing process

Answer

A word that indicates the significance of a document

Answer

A word used to retrieve specific documents

Answer

A word given a high weight in the ranking algorithm

Question 18

Which indexing technique is employed to build an inverted index?

Accepted Answer

Postings list

Answer

Forward index

Answer

Phrase index

Answer

Suffix tree

Question 19

What is the intended purpose of stemming in information retrieval?

Accepted Answer

To reduce words to their root or base form

Answer

To enhance query processing efficiency

Answer

To assign weights to words based on their frequency

Answer

To identify synonyms for a given word

Question 20

What is the significance of relevance feedback in information retrieval?

Accepted Answer

To refine the ranking of search results based on user input

Answer

To identify new keywords for a query

Answer

To eliminate non-relevant documents from the index

Question 21

What is a key advantage of employing distributed information retrieval systems?

Accepted Answer

Scalability and fault tolerance

Answer

Lower hardware requirements

Answer

Enhanced indexing efficiency

Answer

Reduced query response time

Question 22

What is the objective of query expansion techniques in information retrieval?

Accepted Answer

To augment a query with additional terms to enhance its effectiveness

Answer

To reduce the number of terms in a query

Answer

To identify the most relevant documents for a query