adplus-dvertising

Welcome to the Management of Big Semantic Data MCQs Page

Dive deep into the fascinating world of Management of Big Semantic Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Management of Big Semantic Data, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Management of Big Semantic Data, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Big Data Computing.

frame-decoration

Check out the MCQs below to embark on an enriching journey through Management of Big Semantic Data. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Big Data Computing.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Management of Big Semantic Data. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Management of Big Semantic Data MCQs | Page 11 of 15

Explore more Topics under Big Data Computing

Q101.
What is the purpose of the Dictionary component in HDT?

a.

To hold metadata about the data set's publication

b.

To catalog all the different terms used in the data set

c.

To provide statistical information about the data set

d.

To enable query syndication

Discuss
Answer: (b).To catalog all the different terms used in the data set Explanation:The purpose of the Dictionary component in HDT is to catalog all the different terms used in the data set, such as URIs, literals, and blank nodes.
Q102.
How are terms represented in the Dictionary component of HDT?

a.

Terms are represented using plain text

b.

Terms are represented as tuples of three IDs

c.

Terms are represented using binary encoding

d.

Terms are represented as RDF triples

Discuss
Answer: (b).Terms are represented as tuples of three IDs Explanation:In the Dictionary component of HDT, terms are represented as tuples of three IDs that reference the corresponding terms in the dictionary.
Q103.
What is the benefit of representing terms in the Dictionary as IDs?

a.

It allows for plain text representation of terms

b.

It reduces the need for dictionary organization

c.

It saves storage space and enables compression

d.

It simplifies query syntax

Discuss
Answer: (c).It saves storage space and enables compression Explanation:Representing terms in the Dictionary as IDs saves storage space and enables compression, reducing the overall size of the data set.
Q104.
How is the dictionary organized in HDT?

a.

It is organized into sections based on the data set's subjects and objects

b.

It is organized into sections based on the data set's publication metadata

c.

It is organized into sections based on the data set's statistical information

d.

It is organized into sections based on the roles of terms as subjects, predicates, or objects

Discuss
Answer: (d).It is organized into sections based on the roles of terms as subjects, predicates, or objects Explanation:The dictionary in HDT is organized into sections based on the roles of terms as subjects, predicates, or objects.
Q105.
What is the purpose of the shared Subject-Object section in the HDT dictionary?

a.

To store metadata about the data set's publication

b.

To catalog terms that play both subject and object roles in triples

c.

To provide statistics about the data set's usage

d.

To enable direct access to terms in the dictionary

Discuss
Answer: (b).To catalog terms that play both subject and object roles in triples Explanation:The purpose of the shared Subject-Object section in the HDT dictionary is to catalog terms that play both subject and object roles in triples, avoiding repetition in the subjects and objects sections.
Q106.
In HDT, what are the basic operations that must be implemented for handling the dictionary?

a.

Locate, Extract, NumElements

b.

Prefix, Suffix, Substring

c.

Find, Extract, Count

d.

Query, Search, List

Discuss
Answer: (a).Locate, Extract, NumElements Explanation:The basic operations that must be implemented for handling the dictionary in HDT are Locate (term), Extract (id), and NumElements ().
Q107.
What is the purpose of the advanced operations like Prefix, Suffix, Substring, and Regex in HDT's dictionary representation?

a.

They provide metadata about the dictionary

b.

They enable direct access to terms in the dictionary

c.

They are used for efficient compression

d.

They are convenient for tasks like query suggestions and SPARQL query evaluation

Discuss
Answer: (d).They are convenient for tasks like query suggestions and SPARQL query evaluation Explanation:The advanced operations like Prefix, Suffix, Substring, and Regex in HDT's dictionary representation are convenient for tasks like query suggestions and SPARQL query evaluation.
Q108.
What does Front-Coding, a technique used in HDT's dictionary encoding, primarily rely on?

a.

Bitmap indexing

b.

Differential compression

c.

Full-text indexing

d.

Huffman coding

Discuss
Answer: (b).Differential compression Explanation:Front-Coding, a technique used in HDT's dictionary encoding, primarily relies on differential compression.
Q109.
How does Front-Coding work in dictionary encoding?

a.

It divides the dictionary into sections based on roles (subjects, predicates, objects)

b.

It encodes terms in lexicographically sorted buckets and uses differential compression

c.

It stores terms as plain text without any compression

d.

It applies regular expressions to dictionary terms for encoding

Discuss
Answer: (b).It encodes terms in lexicographically sorted buckets and uses differential compression Explanation:Front-Coding in dictionary encoding divides the dictionary into lexicographically sorted buckets and encodes terms using differential compression.
Q110.
What is the advantage of Front-Coding in HDT's dictionary representation?

a.

It provides advanced search capabilities like regular expressions

b.

It is highly efficient for full-text indexing

c.

It simplifies query syntax for SPARQL queries

d.

It offers space/time trade-offs by adjusting bucket size

Discuss
Answer: (d).It offers space/time trade-offs by adjusting bucket size Explanation:The advantage of Front-Coding in HDT's dictionary representation is that it offers space/time trade-offs by adjusting bucket size, making it suitable for different applications and compression needs.
Page 11 of 15

Suggested Topics

Are you eager to expand your knowledge beyond Big Data Computing? We've curated a selection of related categories that you might find intriguing.

Click on the categories below to discover a wealth of MCQs and enrich your understanding of Computer Science. Happy exploring!

Cloud Computing

Stay on top of the biggest trend in IT with our Cloud Computing MCQs. These questions...

Embedded Systems

Dive into the world of specialized computing systems with our Embedded Systems MCQs....

Systems Analysis and Design Methods

Get familiar with the process of designing and improving business systems with our...

Java Programming

Level up your coding skills with our Java Programming MCQs. From object-oriented...

Computer Hardware

Explore the tangible components of computers with our Computer Hardware MCQs. Learn...

Artificial Intelligence

Get started on the path to the future with our Artificial Intelligence MCQs. Covering...

Digital Image Processing (DIP)

Delve into the techniques of enhancing digital images with our Digital Image...

Python

Dive into one of the most popular languages with our Python MCQs. Understand...

Computer Graphics

Step into the visual side of computing with our Computer Graphics MCQs. Cover topics...