Text Summarizer is the product of a modern-day era that has made the content creation processes much simpler. No matter what type of content creation you go for, accurately defining content in a concise manner is necessary. Hence the technology of AI and NLP combines together to deliver a tool that works accurately for us.
In the future of reading and writing, Text Summarizer holds a broader scope for making things easier in terms of convening knowledge or information. And for those who are not familiar with this technology, we are going to give them a brief introduction to it.
In this article, we will state how advanced algorithms and techniques help to build Text summarizers to give accurate results. We will break down the work of the application to show you how the app works. In addition, we will be going through the benefits of using a summarizer to show its scope in the future.
What is a Text Summarizer?
If you have never heard of or used such a tool, then let us give you an overview.
Text Summarizer is an online NLP and AI-based tool that makes your content concise by compiling only the necessary information. The main aim of summarizers is to deliver clear and concise copies of content for conclusions, summaries, introductions, or even descriptions.
Ideally, a summarizer makes it easier for users to point out and use the information that matters. For example, you can use them for some piece of information that needs extensive explanation, but you are bound to explain it in specific words.
How Does it Work?
Now we are going to explain the working of a summarizer by exploring a step-by-step approach towards its technology and how it works. There are various algorithms and techniques involved in analyzing text which is categorized into three crucial types.
Type #1: Input Based
Input-based text summarization is only good for single-page documents or a defined input of words or characters. The input-based summarization analyzes the relation between multiple texts from the same document and compiles it in the form of synthesized information.
As a result, you get a shorter and more concise version of your document’s text. However, this type of summarization is not recommended for multiple pages documents or extensive word count text.
Type #2: Output-Based
The output-based summarization is considered more accurate as it can analyze and process multiple pages from a text-based document. The output-based summarization further involves two different processes called extractive and abstractive text summarization.
The abstractive text summarization generates a uniquely new and fresh presentation of the original text from scratch instead of compiling the original text. Such a type of extraction works with NLP technology, where the machines understand the text and then present the output. The idea is to capture the essence of the text with a deeper understanding of the content.
Extractive text summarization is about selecting the key information from the original text without changing the meaning or context. In this type of summarization, the most crucial sentences or phrases are compiled into a shorter form. Hence you get a clear and concise version of the content featuring the same words and sentences.
Type #3: Purpose Based
The purpose-based summarization aims more at the motive or core area of the content instead of simply focusing on words. For defining the goal or purpose of the content, this type of summarization is further categorized into Informative and argumentative summarization.
Argumentative summarization involves more of an evaluation process while critiquing the arguments presented in a text. That’s where the technology focuses on the strengths and weaknesses of the argument to state the key aspects of the debate in the content.
Informative summarization is the second portion of the purpose based. This type of summarization is much like output-based summarization, which involves an overview of the specified needs and goals defined in the content.
Potential Applications of Text Summarizers in Future
Text Summarization has a broad application and potential to transform the content writing experience. Here we have discussed various areas of life where text summarization has great potential to expand in the near future.
1. Email Summarization
Email marketing and advertisement are based on an elevator pitch that has to be concise and straight. summarization can compile more information in a smaller number of words or characters to make things easier for your client or reader to understand.
2. Product Descriptions
Product descriptions are about defining the services and abilities of the product in a defined number of words. You have to remain to the point of stating what the product is and how it works. Also, you have to compile the features and usability of the product. Hence you can write product descriptions with the text summarization method.
3. Social Media Content
Social media marketing is based on writing attractive captions, about pages, and captions that involve writing content more accurately. Hence you can rely on this technology to write your attractive social media posts by simply telling the AI what to do.
4. Content Marketing
Content marketing and advertising heavily rely on the defined yet accurately stating the products or services via written material. In this case, a conclusion and summary in content marketing can be written with the help of a Text Summarizer to make things easier for you.
5. Legal Document Preparation
The legal document preparation involves stating anything from a legal statement to writing a verdict that defines your motive. In this case, you can rely on a text summarizer that can write the legal statement for you. The summarization process will make the legal statements concise and defined for easily reading the documents and making the point in a valid sense.
AI-based Text Summarizers are evolving in the near future, and almost every day, we get to find a new tool or technology based on writing. Hence the future of Text Summarization is only expanding, and it shows how the demand is evolving by the day. Hopefully, our article was convincing enough to define the working and scope of Text Summarization in the near future.