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Introduction

Natural language generation (NLG) refers to the process of producing human-like text or speech from data or information. In recent years, NLG has gained significant attention due to its potential applications in various fields, including automated news writing. With the rise of digital media and the increasing demand for instant news updates, there is a growing need for automated systems that can generate news articles quickly and accurately.

Background of the Study

The development of NLG systems for automated news writing has been a topic of interest for researchers and practitioners in the fields of artificial intelligence, natural language processing, and journalism. Several studies have explored the potential benefits and challenges of using NLG technology to streamline the news writing process and enhance the quality of news content.

Problem Statement

Despite the potential benefits of NLG for automated news writing, there are still some challenges that need to be addressed. These challenges include the generation of coherent and engaging news stories, the integration of data analysis and storytelling techniques, and the ethical implications of automated news production.

Objective of the Study

The primary objective of this thesis is to explore the use of NLG technology for automated news writing and to develop a prototype system that can automatically generate news articles based on real-time data inputs. The study aims to evaluate the effectiveness and efficiency of the NLG system in producing high-quality news content.

Limitation of Study

This research is limited to the development and evaluation of an NLG system for automated news writing. The study does not cover other aspects of journalism, such as investigative reporting or opinion pieces. Additionally, the study may be limited by the availability of data sources and the quality of the NLG algorithms used in the system.

Scope of Study

The scope of this study includes the design, development, and evaluation of an NLG system for automated news writing. The study will focus on the implementation of data-driven NLG algorithms, the integration of storytelling techniques, and the evaluation of the system’s performance in generating news articles.

Significance of Study

This research has significant implications for the field of journalism and media production. By examining the potential of NLG technology for automated news writing, this study can contribute to the development of more efficient and scalable news production systems. Additionally, the study can provide insights into the ethical considerations and best practices for using NLG technology in journalism.

Structure of the Thesis

This thesis is structured into five chapters. Chapter One provides an introduction to the study, including the background, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter Two presents a literature review on NLG technology and automated news writing. Chapter Three outlines the system design and methodology, while Chapter Four details the system implementation. Finally, Chapter Five presents the conclusion and summary of the project thesis.

Definition of Terms

– Natural Language Generation (NLG): The process of generating human-like text or speech from data or information.
– Automated News Writing: The use of automated systems to produce news articles quickly and accurately.
– Data Analysis: The process of examining, cleaning, transforming, and modeling data to extract useful information.
– Storytelling Techniques: Narrative strategies used to engage and inform audiences in news articles.

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