Challenge Your Skills: Information Retrieval Quiz

Reviewed by Godwin Iheuwa
Godwin Iheuwa, MS (Computer Science) |
Computer Science
Review Board Member
Godwin is a proficient Database Administrator currently employed at MTN Nigeria. He holds as MS in Computer Science from the University of Bedfordshire, where he specialized in Agile Methodologies and Database Administration. He also earned a Bachelor's degree in Computer Science from the University of Port Harcourt. With expertise in SQL Server Integration Services (SSIS) and SQL Server Management Studio, Godwin's knowledge and experience enhance the authority of our quizzes, ensuring accuracy and relevance in the realm of computer science.
, MS (Computer Science)
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Challenge Your Skills: Information Retrieval Quiz - Quiz

We have come up with an amazing information retrieval quiz for you. Information retrieval is understood as the science of searching for information in a document, also searching for documents themselves, as well as searching for the metadata (data that describes data) and databases of texts, images, or sounds. So, do you think you know enough to pass this test? Let's find out right now! Best of luck to you!


Information Retrieval Questions and Answers

  • 1. 

    A large repository of documents in IR is called:

    • A.

      Corpus

    • B.

      Database

    • C.

      Dictionary

    • D.

      Collection

    Correct Answer
    A. Corpus
    Explanation
    A large repository of documents in Information Retrieval (IR) is called a corpus. A corpus refers to a collection of texts or documents that are used for linguistic analysis or research purposes. It typically includes a wide range of texts from various sources, such as books, articles, websites, or any other form of written material. By analyzing a corpus, researchers can gain insights into language patterns, trends, and usage, which can be beneficial for various fields like natural language processing, computational linguistics, and information retrieval itself.

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  • 2. 

    The posting list should be sorted by:

    • A.

      Document Frequency

    • B.

      DocID

    • C.

      TermID

    • D.

      Term frequency

    Correct Answer
    B. DocID
    Explanation
    The posting list should be sorted by DocID because it ensures that the documents are listed in a consistent and organized manner. Sorting by DocID allows for easier retrieval and comparison of documents, as it provides a unique identifier for each document. Additionally, sorting by DocID can improve the efficiency of certain operations, such as merging or intersecting multiple posting lists.

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  • 3. 

    For query optimization, while intersecting two posting list, we should

    • A.

      Process in the order of increasing document frequency

    • B.

      Process in any order

    • C.

      Process in the order of decreasing document frequency

    • D.

      None of the above

    Correct Answer
    A. Process in the order of increasing document frequency
    Explanation
    When optimizing a query, it is more efficient to intersect two posting lists in the order of increasing document frequency. This means processing the posting lists that have lower document frequencies first. By doing so, we can eliminate irrelevant documents early on in the process, reducing the overall number of comparisons needed and improving the query's performance.

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  • 4. 

    Term-document incidence matrix is:

    • A.

      Dense

    • B.

      Sparse

    • C.

      Depends on the data

    • D.

      Cannot predict

    Correct Answer
    B. Sparse
    Explanation
    The term-document incidence matrix is described as "sparse" because it typically contains a large number of zeros. In this matrix, the rows represent terms and the columns represent documents, with each entry indicating the presence or absence of a term in a document. Since most documents only contain a small subset of all possible terms, the matrix is sparse, meaning that the majority of its entries are zeros. This sparsity allows for efficient storage and processing of the matrix, making it a commonly used representation in information retrieval and text mining tasks.

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  • 5. 

    Lemmatization is a technique for:

    • A.

      Ranking documents

    • B.

      Case folding

    • C.

      Normalization

    • D.

      Tokenization

    Correct Answer
    C. Normalization
    Explanation
    Lemmatization is a technique used for normalization. It involves reducing words to their base or root form, which helps in grouping together different forms of the same word. This process ensures that variations of a word are treated as the same word, making it easier for analysis and comparison. Normalization is an important step in natural language processing tasks like information retrieval, text mining, and machine learning. It helps in improving the accuracy and efficiency of these tasks by reducing the complexity of the text data.

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  • 6. 

    A model of information retrieval in which we can pose any query in which search terms are combined with the operators AND, OR, and NOT:

    • A.

      Ad hoc retrieval model

    • B.

      Ranked retrieval model

    • C.

      Boolean retrieval model

    • D.

      Proximity query model

    Correct Answer
    C. Boolean retrieval model
    Explanation
    The Boolean retrieval model is a model of information retrieval that allows us to pose queries using search terms combined with the operators AND, OR, and NOT. This model is based on Boolean logic, where the search results are either true or false based on the presence or absence of the search terms in the documents. It is a simple and straightforward approach to information retrieval, where the focus is on exact matches of the search terms rather than relevance ranking.

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  • 7. 

    The number of times that a word or term occurs in a document is called:

    • A.

      Document frequency

    • B.

      Collection frequency

    • C.

      Term frequency

    • D.

      Indexing granularity

    Correct Answer
    C. Term frequency
    Explanation
    Term frequency refers to the number of times a word or term appears in a document. It is a measure of how frequently a specific term occurs within a document and is commonly used in information retrieval and natural language processing tasks. By calculating the term frequency, we can determine the importance or relevance of a term within a document or a collection of documents.

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  • 8. 

    Stemming increases the size of the vocabulary.

    • A.

      True

    • B.

      False

    Correct Answer
    B. False
    Explanation
    Stemming does not increase the size of the vocabulary. In fact, stemming reduces words to their base or root form, which helps in consolidating similar words and reducing the overall vocabulary size. Stemming aims to normalize words so that variations of the same word can be treated as a single entity, thereby improving text analysis and information retrieval tasks. Therefore, the statement that stemming increases the size of the vocabulary is false.

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  • 9. 

    A crude heuristic process that chops off the ends of the words to reduce inflectional forms of words and reduce the size of the vocabulary is called:

    • A.

      Lemmatization

    • B.

      Case folding

    • C.

      True casing

    • D.

      Stemming

    Correct Answer
    D. Stemming
    Explanation
    Stemming is a crude heuristic process that reduces inflectional forms of words by chopping off the ends of the words. This process helps to reduce the size of the vocabulary by grouping together words that have the same root or stem. Unlike lemmatization, which aims to reduce words to their base or dictionary form, stemming focuses on removing prefixes and suffixes to obtain the stem of a word. Case folding refers to converting all letters to lowercase, while true casing preserves the original case of words. Therefore, the correct answer for this question is stemming.

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  • 10. 

    In information retrieval, extremely common words that would appear to be of little value in helping select documents and are excluded from the index vocabulary are called:

    • A.

      Stop words

    • B.

      Tokens

    • C.

      Lemmatized words

    • D.

      Stemmed terms

    Correct Answer
    A. Stop words
    Explanation
    Stop words are extremely common words that are excluded from the index vocabulary in information retrieval. These words, such as "and," "the," and "is," appear frequently in text but do not carry much meaning in terms of document selection. By excluding stop words from the index, the retrieval system can focus on more important and meaningful terms.

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Godwin Iheuwa |MS (Computer Science) |
Computer Science
Godwin is a proficient Database Administrator currently employed at MTN Nigeria. He holds as MS in Computer Science from the University of Bedfordshire, where he specialized in Agile Methodologies and Database Administration. He also earned a Bachelor's degree in Computer Science from the University of Port Harcourt. With expertise in SQL Server Integration Services (SSIS) and SQL Server Management Studio, Godwin's knowledge and experience enhance the authority of our quizzes, ensuring accuracy and relevance in the realm of computer science.

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  • Current Version
  • Mar 31, 2024
    Quiz Edited by
    ProProfs Editorial Team

    Expert Reviewed by
    Godwin Iheuwa
  • Aug 29, 2019
    Quiz Created by
    Vaishali
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