Text Summarization
In The Future, Technology Is Developing Very Fast
IN THE FUTURE LANGUAGE TECHNOLOGY TO BECOME PREVALENT IN THE INDUSTRY
Future technology that will be developed is the consequence of technical innovative in the field of Machine Learning, Artificial Intelligence, Large Language Models and Natural Language Processing (NLP) Technology.
Types of Text Summarization
There are two main types of text summarization
Extractive Summarization
This type of summarization extracts the most important sentences from the original document and creates a summary from those.
Abstractive Summarization
This type of summarization creates a summary that is not simply a collection of sentences from the original document. Instead, the summary is rewritten in a way that captures the main ideas of the document.
Text Summarization Techniques
- Keyword Extraction: This technique identifies the most important keywords in a document and creates a summary from those keywords.
- Sentence Scoring: This technique assigns a score to each sentence in a document based on its importance. The sentences with the highest scores are then used to create a summary.
- Topic Modeling: This technique identifies the topics in a document and creates a summary that covers all of the topics.
- Machine Learning: This technique uses machine learning algorithms to learn how to create summaries from documents.
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Benefits of Text Summarization
Overview
A summary of a document can provide a quick overview of the document, which can be helpful for people who are short on time or who are not interested in reading the entire document.
Conciseness
A summary of a document can be more concise than the original document, which can save time and space.
Conciseness
A summary of a document can be more concise than the original document, which can save time and space.
Improved readability
A summary of a document can be easier to read than the original document, especially if the original document is long or complex.
