[ad_1]

Introduction

In the era of big data and artificial intelligence, knowledge graphs have emerged as a powerful tool for organizing and extracting insights from complex, interconnected data sources. Knowledge graphs are semantic networks that capture relationships between entities in a specific domain, enabling advanced data analytics and reasoning. In the context of the Semantic Web, knowledge graphs play a crucial role in facilitating the interoperability and integration of heterogeneous data sources.

Background of study

The Semantic Web is an extension of the World Wide Web that enables machines to understand and process information in a more structured and meaningful way. Knowledge graphs are a key component of the Semantic Web architecture, providing a shared, machine-readable representation of knowledge that can be used by intelligent applications.

Problem Statement

Despite the potential benefits of knowledge graphs for semantic web applications, there are still many challenges and open research questions that need to be addressed. These include issues related to knowledge graph construction, integration, maintenance, and scalability.

Objective of study

The main objective of this thesis is to investigate the use of knowledge graphs for semantic web applications and to propose novel methods and techniques for addressing the challenges and limitations in this area.

Limitation of study

Due to the complexity and breadth of the topic, this thesis will focus on a specific aspect of knowledge graphs for semantic web applications, namely knowledge graph construction and querying.

Scope of study

The scope of this study will include a review of existing literature on knowledge graphs and semantic web applications, the design and implementation of a knowledge graph framework, and an evaluation of the proposed methods using real-world data.

Significance of study

This research is significant as it contributes to the advancement of knowledge in the field of semantic web applications and provides practical insights for researchers and practitioners working in this area.

Structure of the Thesis

This thesis is organized into five chapters. Chapter one provides an introduction to the topic, including the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter two presents a comprehensive literature review on knowledge graphs and semantic web applications. Chapter three details the research methodology, including data collection, analysis, and evaluation. Chapter four discusses the findings of the study and their implications. Finally, chapter five concludes the thesis and summarizes the key findings and contributions.

Definition of terms

– Knowledge graphs
– Semantic web
– Data integration
– Data analytics
– Machine reasoning
– Interoperability
– Heterogeneous data sources
– Knowledge graph construction
– Querying techniques
– Real-world data

Thesis Overview

Knowledge graphs have become increasingly popular in the field of semantic web applications, providing a powerful way to organize and extract insights from complex data. This thesis aims to investigate the use of knowledge graphs in semantic web applications and propose novel methods and techniques for addressing the challenges in this area.

Chapter two will provide a comprehensive literature review on knowledge graphs and semantic web applications, highlighting the existing research and identifying gaps in the literature. Chapter three will detail the research methodology, including data collection, analysis, and evaluation. Chapter four will discuss the findings of the study and their implications, presenting the proposed methods and techniques.

Overall, this thesis will contribute to the advancement of knowledge in the field of semantic web applications by providing practical insights and solutions for researchers and practitioners in this area.

[ad_2]

---

Purchase Detail

Download the complete project materials to this project with Abstract, Chapters 1 – 5, References and Appendix (Questionaire, Charts, etc), Click Here to place an order via whatsapp. Got question or enquiry; Click here to chat us up via Whatsapp.
You can also call 08111770269 or +2348059541956 to place an order or use the whatsapp button below to chat us up.
Bank details are stated below.

Bank: UBA
Account No: 1021412898
Account Name: Starnet Innovations Limited

The Blazingprojects Mobile App

Download and install the Blazingprojects Mobile App from Google Play to enjoy over 50,000 project topics and materials from 73 departments, completely offline (no internet needed) with monthly update to topics, click here to install.