MCQ Bank

MongoDB uses the String BSON data type to store textual data. Unlike relational databases, MongoDB does not use types such as VARCHAR or VARCHAR2 for strings.

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Q48

Which one is not common observation about NoSQL Databases?

A) Built for the 21st century web estates
B) Running well on clusters
C) Mostly open-source
D) Schema Oriented

AI Explanation

NoSQL databases are generally characterized by flexible or schema-less data models rather than being schema-oriented. They are commonly designed for web-scale applications, cluster environments, and are often open-source.

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Q49

_______________________ is a classification algorithm.

A) K-Means
B) Naïve Bayes
C) Density-based Method
D) Hierarchical Method

AI Explanation

Naïve Bayes is a supervised classification algorithm that uses Bayes' theorem to assign observations to classes. K-Means, density-based methods, and hierarchical methods are primarily used for clustering.

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Q50

_______________ is an example of NoSQL database.

A) MS Access
B) Oracle
C) DB2
D) Neo4j

AI Explanation

Neo4j is a NoSQL graph database designed to store and query data as nodes and relationships. MS Access, Oracle, and DB2 are relational database systems.

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Q51

A table in Relational Database Management System is called _____________ in MongoDB.

A) Page
B) Collection
C) Embedded Document
D) Document

AI Explanation

In MongoDB, a collection is roughly equivalent to a table in a relational database. Collections contain documents rather than rows.

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Q52

____________ is not a supervised learning approach.

A) Voice Recognition
B) Labeling
C) Clustering
D) Classification

AI Explanation

Clustering is an unsupervised learning approach because it identifies groups or patterns in data without predefined labels. Classification and labeling are supervised approaches.

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Q53

________________ deals with finding a structure in a collection of unlabeled data.

A) Voice Recognition
B) Labeling
C) Clustering
D) Classification

AI Explanation

Clustering finds meaningful structures or groups within a collection of unlabeled data. It does not require predefined class labels, making it an unsupervised learning technique.

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Q54

K-Means works only for ________ data.

A) Binary
B) Time
C) Text
D) Numerical

AI Explanation

K-Means clustering operates on numerical feature values and uses distance measures to assign observations to clusters. Standard K-Means is therefore designed for numerical data.

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Q55

_______ uses Mahout for user interest modeling.

A) Facebook
B) Twitter
C) Instagram
D) Yahoo

AI Explanation

Twitter used Apache Mahout for recommendation and user-interest modeling applications. Mahout provides scalable machine-learning algorithms that can process large datasets.

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Q56

__________ is a Clustering Algorithm.

A) K-Means
B) Decision Tree based Methods
C) Naïve Bayes
D) Neural Networks

AI Explanation

K-Means is a widely used clustering algorithm that groups data points according to similarity. Decision trees, Naïve Bayes, and neural networks are primarily used for supervised learning tasks such as classification.

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Q57

MongoDB is an example of ____________________ NoSQL database.

A) Columnar Database
B) Graph Database
C) Key Value Database
D) Document Store

AI Explanation

MongoDB is a document-oriented NoSQL database. It stores data in flexible BSON documents rather than rows and columns of relational tables.

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Q58

In Mahout, Data object hold a file that does not contain ________.

A) Users
B) Preferences details of a product
C) Items
D) Items Price

AI Explanation

In Mahout's recommendation data model, the data object contains information such as users, items, and user preferences or preference values. An item's price is not a required component of the basic preference data.

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Q59

_________is the process by which we gather pages from the Web, in order to index them and support a search engine.

A) Web Server
B) Search Engine
C) Web Application
D) Web Crawling

AI Explanation

Web crawling is the process of systematically gathering web pages for indexing and search. A crawler discovers pages and follows links to collect additional content for a search engine.

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Q60

In Indexing, most common words of vocabulary are called ______ words.

A) Frequent
B) Start
C) Famous
D) Stop

AI Explanation

In information retrieval, the most common and frequently occurring words are known as stop words. Examples include common words such as “the,” “is,” and “of,” which are often removed during indexing.

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Q61

Which of the following is the correct output of the 10001 AND 11011 AND 10101?

A) 10001
B) 10101
C) 10101
D) 11010

AI Explanation

The AND operation returns 1 only when the corresponding bit is 1 in all operands. For 10001 AND 11011 AND 10101, the result is 10001 AND 11011 = 10001, and then 10001 AND 10101 = 10001. Therefore, the correct output is 10001.

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Q62

Which of the following is NOT a method/strategy of Indexing?

A) Boolean Index
B) Converted Index
C) Inverted Vectors
D) Inverted Index

AI Explanation

Boolean Index, Inverted Vectors, and Inverted Index are recognized indexing methods or strategies. Converted Index is not a standard indexing method.

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Q63

IDF stands for:

A) Inverse Document Frequency
B) Inverted Deficiency Frequency
C) International Distributed Frequency
D) Inverse Digital Frequency

AI Explanation

IDF stands for Inverse Document Frequency. It measures how rare or informative a term is across a collection of documents and is commonly used in TF-IDF weighting.

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Q64

__________is a software tool used to access and search information on the web.

A) Web browser
B) Web server
C) MS Excel
D) MS Word

AI Explanation

A web browser is software used to access, retrieve, and search information on the World Wide Web. Web servers provide web content, while MS Excel and MS Word are productivity applications.

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Q65

_______ are more informative than _________ terms.

A) Frequent terms, rare
B) Rare terms, frequent
C) Regular terms, non regular
D) Important terms, non important

AI Explanation

Rare terms are generally more informative because they distinguish documents more effectively. Frequent terms appear in many documents and therefore provide less discriminatory information.

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Q66

The ________collects, parse, and stores data to facilitate fast and accurate information retrieval.

A) Indexing stage
B) Storing stage
C) Collecting stage
D) Parsing stage

AI Explanation

The indexing stage collects, parses, and stores data in an index to support fast and accurate information retrieval. It organizes information so that relevant documents can be located efficiently.